Input: Task: corroborate the claim using the given text. Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: The increase in temperature with depth in the Earth’s crust can be expressed in terms of what is known as the geothermal temperature gradient. Down to the depths accessible by drilling with modern technology (e. g. over 10 km), the average geothermal gradient is about 2. 5-3. 0 oC/100 m (Dickson& Fanelli, 2005). For example, at depth around 3 km below ground level, the temperature is about 90 oC. There are, however, areas in which the geothermal gradient is far from the average value (e. g. in some geothermal areas the gradient is ten times the average value) due to geothermal structure and composition of these areas (Dickson& Fanelli, 2005). The type of geothermal resource determines the type of system and method of its harvesting and utilization for electrical power generation. For example, high-temperature geothermal resources (vapour- and liquid-dominated) can be harvested and utilized to generate electricity using one of the following methods depending on the compositional and thermal characteristics of the resource: (1) single-flash steam power systems, (2) double-flash steam power systems, and (3) dry-steam power systems. Generating electricity from medium- and low-temperature geothermal resources (i. e. water-dominated resources) can be efficiently accomplished using a Binary-cycle technique, such as, ORC (Ismail, 2011a; Chandrasekharam& Bundschuh, 2008; Dickson & Fanelli, 2005; DiPippo, 2008). Generating electricity from geothermal steam resources using an experimental 10 kW-electrical generator was made at Larderello of Italy in 1904 (Dickson& Fanelli, 2005; Panea et al. , 2010). The commercial success of this attempt indicated the industrial value of geothermal energy and marked the beginning of a form of exploitation that was to develop significantly from the on. By 1942, the installed geothermal-electric capacity had reached approximately 128 MWe (Dickson& Fanelli, 2005). In the early 1950’s, many countries were attracted by geothermal energy, considering it to be economically competitive with other forms of energy. It was estimated (Dickson& Fanelli, 2005; Ruggero, 2007) that the worldwide installed geothermal-electric capacity reached 1. 300 GWe (in 1975), 4. [SEP] Justify:

Output: The text corroborates the claim by describing how geothermal energy is generated from the heat beneath the Earth's surface. It mentions the geothermal temperature gradient and provides specific examples of how various types of geothermal resources can be harnessed for electrical power generation, explaining the methods used in this process, such as single-flash and binary-cycle techniques.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: Microbiome composition and presence of cultivable commensal groups of (Tamandua tetradactyla) varies with captive conditions access Published: 02 May 2024 Microbiome composition and presence of cultivable commensal groups of (Tamandua tetradactyla) varies with captive conditions Ahmad Amin1, Chahrazed Mekadim2, Nikol Modrackova1, Petra Bolechova3, Jakub Mrazek2 & …Vera Neuzil-Bunesova1 Show authors 1. For each animal, 3 samples were collected and analyzed at weekly intervals. Table 1 The list of anteaters, including locations, captive conditions, and intervals of fecal samplingFull size table16S rRNA gene amplicon sequencingTotal genomic DNA was extracted from 300 mg of fecal samples (FS; from three FS per one animal collected independently in intervals as shown in Table 1; 100 mg per each FS) using the QIAamp® PowerFecal® Pro DNA Kit (Qiagen, Germany) according to the manufacturer’s instructions. The extracted DNA was then used as a template for the preparation of amplicons from the V4 region of the 16S rRNA gene [14]. Libraries were prepared from the purified amplicons using the kit (), according to Milani et al. [15]. The sequencing was then performed on the platform () as it was described previously by Mekadim et al. [16]. Microbiome analysesThe obtained bacterial 16S rDNA sequences in FASTQ format were analyzed by QIIME 2 version 2022. 2 pipeline [17]. Quality filtering of sequences and removal of chimaera were performed using the DADA2 [18] to obtain amplicons sequence variants (ASVs) using the method of denoise-pyro which denoises single-end sequences with trimming left of 15 and maximum length of 250. Mafft was used to align the sequences [19] and fasttree was used to construct a phylogenetic tree [20]. Then, ASVs were taxonomically classified using based on SILVA database (release 138) with a 99% threshold [15], query alignment coverage of 0. 8 and maxaccepts and maxhits values were set at 1. The rarefaction was performed based on the sequence depth to normalize data. [SEP] Justify:

Output: The text contrasts the claim by discussing the variability in microbiome composition in Tamandua tetradactyla, indicating that microbiome composition varies with factors such as captive conditions. This implies that microbiome compositions are not identical across individuals.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: Distinct dopaminergic neurons may have different roles in larval aversive learningPrevious work reported that aversive olfactory learning was induced through the optogenetic activation of DAN-d1, f1, or g1, but not DAN-c185. This discrepancy can be explained as the optogenetic overexcitation of DAN-c1, similar to our optogenetic or D2R knockdown results. Our learning assay results from larvae with D2R knockdown in DAN-d1 or g1 also supported this: aversive learning was not affected by D2R knockdown (Figure S4E). These data indicate D2Rs in DAN-d1 or g1 are not involved in larval aversive learning. Additionally, the DAN-c1 strain used in the previous work (SS02160-split-GAL4) not only labels DAN-c1, but also marks other non-dopaminergic neurons, which may affect the results. Besides, live calcium imaging showed that DAN-d1, f1, and g1 responded to the activation of mechanosensory and nociceptive neurons85, indicating a functional differentiation from gustatory activated DAN-c162,86. In future studies, the molecular signaling downstream of D2R needs to be explored, as well as the comprehensive neuronal circuit architectures of larval learning. The neuronal circuits underlying learning and memory are complex networks, sharing similarities with the regulatory networks of gene expression. Studies of the mechanisms of learning and memory help us understand the essential principles of the non-linear dynamic characteristics in these complex systems. On one hand, the progress in larval learning provides useful information for helping our understanding about more complex systems, from brains in adult flies to those in mammals. On the other hand, the architecture of larval learning circuits could improve either hardware design or algorithm structures in artificial intelligence, which may bring more powerful tools, such as navigation systems regulating multiple auto-drive vehicles in complex 3-dimentional environments. In conclusion, we explored the expression pattern of D2R in the third-instar larval brain and investigated their roles during larval olfactory learning. D2Rs were found in DAN-c1, and their knockdown induced deficiency in aversive learning. D2Rs were also expressed in MBNs, knockdown of which impaired both aversive and appetitive learning. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the roles of dopaminergic neurons in larval aversive learning and does not mention olfactory receptors or quantum effects. It focuses on the neural circuits involved in learning rather than any quantum phenomena related to olfactory receptors.


Input: Task: corroborate the claim using the given text. Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: 764 GWe (in 1985), 6. 833 GWe (in 1995), 7. 974 GWe (in 2000), 8. 806 GWe (in 2004), 8. 933 GWe (in 2005), 9. 732 GWe (in 2007). In 2010, it was reported (Holm et al. , 2010) that 10. 715 GWe is online generating 67,246 GWh which represents a 20% increase in geothermal power online between 2005 and 2010. While power on-line grew 20% between 2005 and 2010, countries with projects under development grew at a much faster pace. In 2007, Association (GEA) reported that there were 46 countries considering geothermal power development. In 2010, this report identified 70 countries with projects under development or active consideration, a 52% increase since 2007. It should be noted that projects under development grew the most intensely in two regions of the world; namely, Europe and Africa (Holm et al. , 2010). Very recently, it was reported (GEA, 2012) that as of May 2012, approximately 11. 224 GWe of installed geothermal-electric power capacity was online globally, and is increasingly contributing to the electric power supply worldwide. It was estimated (Ruggero Bertani, 2007) that geothermal energy provides approximately 0. 4% of the world global power generation, with a stable long term growth rate of 5%; the largest markets being in and Italy. Security for long-term electricity supply and GHG emission from fossil fuelled power plants is becoming a cause of concern for the entire world today. It was estimated (Chandrasekharam& Bundschuh, 2008) that the world net electricity demand is going to increase by approximately 85% from 2004 to 2030, rising from 16,424 TWh (in 2004) to 30,364 TWh in the year 2030. It was also reported (Chandrasekharam& Bundschuh, 2008; Dickson & Fanelli, 2005) that the emissions of GHG from geothermal power plants constitute less than 2% of the emission of these gases by fossil-fuelled power plants. [SEP] Justify:

Output: The text corroborates the claim by discussing the global capacity and growth rate of geothermal energy, indicating its role in power generation. For instance, it mentions the installed geothermal-electric power capacity and how it contributes to the electric power supply worldwide, which is aligned with the definition of harnessing heat from beneath the Earth's surface for energy.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: Alpha diversity was determined using Shannon and Simpson diversity indexes based on the Kruskal–Wallis test. Analysis (PCoA) was based on Bray–Curtis distance (beta diversity). The box plots for alpha diversity and the 2-dimensional PCoA plots were generated in R-Studio ( using qiime2R ( and ggplot2 ( packages. Permutational multivariate analysis of variance (Adonis) and Bray–Curtis distance matrix were used to evaluate the dissimilarity among location groups with permutation set at 999. The linear discriminant analysis with effect size (LEfSe) algorithm was performed [21] in Galaxy module to identify bacterial families with significant differential relative abundances between location groups based on the factorial Kruskal–Wallis (KW) test and the pairwise Wilcoxon test with α value of 0. 05 and threshold value of 2. 0. Cultivation analysis of fecal samplesFS collection and cultivation analysis were performed according to Modrackova et al. [22] with some modifications. FS were collected in tubes containing a dilution buffer (5 g L−1 tryptone, 5 g L−1 nutrient broth No. 2, 2. 5 g L−1 yeast extract (all Oxoid, Basingstoke, UK), 0. 5 g L−1 L-cysteine, 1 mL L−1 Tween 80 (both Sigma-Aldrich, St. Louis, Missouri, USA), 30% glycerol (), and glass pearls for homogenization. Media were prepared in an oxygen‐free carbon dioxide environment and then sterilized. After sampling, the tubes were stored at – 20 °C and were transported to the laboratory for analysis within 1 month. Decimal serial dilutions of FS were then spread on the following media. Wilkins–Agar was supplemented with 5 g L−1 GMO-Peptone (both Oxoid), 0. 5 g L−1 L-cysteine, and 1 mL L−1 Tween 80 to determine total counts of anaerobic bacteria (WSP medium). Three variants of selective media were used for clostridial/bifidobacterial quantification and isolation. [SEP] Justify:

Output: The text contrasts the claim because it discusses the evaluation of dissimilarities in microbiome compositions across location groups using various statistical analyses (e.g., Adonis test, Bray-Curtis distance). These methods imply that there are differences in microbiome compositions rather than everyone sharing an identical microbiome.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: This research revealed the important roles of D2Rs in Drosophila larval olfactory learning and enriched our understanding regarding the mechanisms underlying the learning process. Materials and MethodsFly stocksAll fly strains used in this study are listed in Table 1 and Table S1. Flies were maintained on standard medium, which consists of cornmeal, yeast, dextrose, sucrose and agar in water. Flies were kept in a 12/12-hour light/dark cycle at 25°C. Canton-S genotype (WT) and yw1118 were used as wild-type. Strains carrying more than one transgene were constructed by standard genetic crosses with the w1118; CyO/Sco; TM2/TM6 multiple balancer chromosome strain. Strain UAS-Syb::spGFP1-10, LexAop-CD4::GFP11, LexAop-rCD2::RFPCyO; MB247-LexA::Up16/TM6B was made by chromosome swapping between UAS-Syb::spGFP1-10, LexAop-CD4::GFP11/CyO (II, second chromosome) and LexAop-rCD2::RFP (II). The D2R gene is located on the X chromosome, with 6 different alternative splicing products. The GFP-tagged D2R strain is inserted with a GFP gene in the second intron, generating D2R molecules tagged with GFP87,88. The D2R-miR strain produces microRNA recognizing the sequence across the third and fourth exons, which is not affected by the GFP insertion (Figure S4F). -GFP reconstitution across synaptic partners (GRASP) was used to investigate whether neurons formed synapses89 (Figure S2d). Half of split GFP tethered to the presynaptic synaptobrevin (UAS-syb::spGFP1-10) was expressed in one type of neuron using UAS/Gal4 binary system, and the complementary split GFP linked to a membrane protein (LexAop-CD4::spGFP11) was expressed in another category of neuron with LexA/LexAop. [SEP] Justify:

Output: The text discusses research focused on D2 receptors in Drosophila larval olfactory learning, detailing experimental methods and genetic strains. However, it does not address olfactory receptors functioning through quantum effects and is therefore irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: To meet future energy demands renewable energy sources should meet the following criteria (Chandrasekharam& Bundschuh, 2008): (1) the sources should be large enough to sustain a long-lasting energy supply to generate the required electricity for the country, (2) the sources should be economically and technically accessible, (3) the sources should have a wide geographic distribution, and (4) the sources should be environmentally friendly and thus should be low GHG emitters in order to make significant contribution to global warming mitigation. Low-temperature (low-enthalpy) geothermal energy resources meet all the above criteria. It was reported in (Chandrasekharam& Bundschuh, 2008; Cui et al. , 2009) that this huge low-temperature geothermal energy resource has already been used for power generation by typical countries, such as and Austria. The installations of several commercial low-temperature geothermal power systems in these countries have substantially proved the ability of low-temperature geothermal fluids to generate green electricity (Chandrasekharam& Bundschuh, 2008). In most developing countries, low-temperature geothermal resources have not received much attention for electricity generation. The main reason for not utilizing these resources by most developing countries (and several industrialized countries) for commercial exploitation is that they are not considered as economically feasible for generating electricity (Chandrasekharam& Bundschuh, 2008). In contrast, in some industrialized countries, especially USA and in Europe, increasing energy demand and environmental awareness related to climate change have urged these countries to develop technologies which utilize low-temperature geothermal resources economically for power generation (Chandrasekharam& Bundschuh, 2008; Dickson & Fanelli, 2005). It was reported (Chandrasekharam& Bundschuh, 2008; Galanis et al. , 2009) that developing countries, in general, need to benefit from these new and continually improving technologies for using low-temperature geothermal resources for generating electricity. It should be noted that for many developing countries, the use of low-temperature geothermal resources is not new. Many of developing countries have been using these resources for the past centuries for direct heating (but not power generation) applications (Chandrasekharam& Bundschuh, 2008). [SEP] Justify:

Output: The text corroborates the claim by discussing the use of low-temperature geothermal energy resources for power generation. It highlights the ability of these resources to generate green electricity and states that several commercial low-temperature geothermal power systems have been installed in countries like Austria and the USA. Additionally, it discusses the potential of these geothermal resources to meet growing energy demands while being environmentally friendly, thus supporting the idea that geothermal energy harnesses heat from beneath the Earth’s surface for power generation.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: The purity was then checked by phase-contrast microscopy (E200, Japan) in all tested bacterial isolates, which were later identified to the species level using Matrix-Desorption/Spectrometry (MALDI-TOF MS) using an ethanol-formic acid extraction procedure with an HCCA matrix solution according to the manufacturer’s instructions () and Modrackova et al. [24]. Data accessibilitySequences of raw data files have been deposited in the NCBI database under Archive (SRA) accession numbers: SUB13811158 and BioProject ID: PRJNA1011505. ResultsMicrobiome alpha and beta diversityIn total, the microbiomes of eleven (Tamandua tetradactyla) from four different locations and captive conditions were analyzed. Three independent FS per each animal were used when DNA was isolated (Table 1). The results of alpha diversity using Shannon and Simpson diversity indexes are represented in the boxplot graph (Fig. 1). These differing values are reported in (Additional file 1: Table S1). Fig. 1Microbiome diversity analysis of fecal samples of captive from different locations. Boxplots illustrating alpha diversity using Shannon and Simpson diversity indices in bacterial community across different locations. P value ≤ 0. 05 was considered statistically significant based on the Kruskal–Wallis testFull size imageThe highest bacterial diversity was observed in the gut microbiome of animals from location L3 using both Shannon and Simpson indexes. index, the diversity of gut microbiome of animals from location L3 was significantly higher in comparison to animals from location L1 (P = 0. 017) but the difference was not significant in comparison to animals from locations L2 and L4 (P > 0. 05). The diversity of gut microbiome of animals from location L1 was significantly low in comparison with the diversity of the gut microbiome of animals from other locations L2 (P = 0. 019 in both indexes), L3 (P = 0. 003 Shannon index, P = 0. 017 Simpson index), and L4 (P = 0. 027 Shannon index, P = 0. 006 Simpson index). However, no significant difference was observed between animals from L2 and L4 locations using both indexes (P > 0. 05). Principal coordinate analysis (PCoA) based on Bray–Curtis distance was performed to compare the diversity of the fecal microbiome of anteater at different locations (Fig. 2). [SEP] Justify:

Output: The text contrasts the claim by indicating that the gut microbiome diversity varies significantly among animals from different locations, as demonstrated by the differences in Shannon and Simpson diversity indices. The study highlights that microbiome samples from location L3 exhibited the highest diversity, while those from location L1 were significantly less diverse, clearly showing that microbiome compositions are not identical among individuals.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: If synapses between these neurons exist, the split GFPs would form a complete one and be recognized by a mouse antibody (Figure S2a-c). ImmunohistochemistryAll staining processes were performed in 1. 5 ml Eppendorf tubes. Late third-instar (96-100h after egg laying) larval brains were dissected in dissection solution (300 mOsmol/L). Brains were fixed in 4% paraformaldehyde (. No. 15713) for 1 hour on ice. After three washes (0. 1% bovine serum albumin in 10m9647), brains were incubated in the blocking and permeabilization solution (0. 2% Triton X-100 in 10mM PBS with 5% normal goat serum; Triton-X 100, Sigma, T8532; NGS, Sigma-Aldrich, G9023) for 2 hours at room temperature. Incubation with primary antibodies was done overnight at 4°C. After three washes, brains were incubated in the secondary antibodies for two hours. Both the primary and secondary antibodies were diluted in the blocking and permeabilization solution. GFP antibody (Rabbit, Scientific, Cat. No. A6455, 1:1000), TH antibody (Mouse, Immunostar, Cat. No. 22941, 1:1000), goat anti-rabbit with green fluorescence (Invitrogen, 488 conjugate, Cat. No. A-11035, 1:1000), and goat anti-mouse IgG with far-red fluorescence (633 conjugate, Cat. No. 21052, 1:500) secondary antibodies were used. After three washes, brains were transferred and mounted in the Fluoro-Gel with (Sciences, Cat. No. 17985-10) on a piece of micro cover glasses (Sciences, Cat. No. 72200-41). Finally, the samples were covered with another piece of micro cover glasses. A seven-day staining protocol was used for staining of GFP-tagged D2R or GRASP, in which brains were fixed in 1% paraformaldehyde in Schneider’s insect medium (Sciences, Cat. NO. S0146) overnight at 4°C. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the technical details of a staining protocol for immunohistochemistry involving GFP and various antibodies, without any mention or implication regarding olfactory receptors or quantum effects.


Input: Task: corroborate the claim using the given text. Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: Recent increases in the cost and uncertainty of future conventional energy supplies for power generation are improving the attractiveness of low-temperature geothermal resources. Continuous development of innovative drilling and power generation technologies makes this nonconventional, renewable and clean energy source the best future viable, alternate and available source to meet the required future electricity demand worldwide, significantly reducing GHG emissions and mitigating global climate change (Chandrasekharam& Bundschuh, 2008). As mentioned earlier, generating electricity from low-temperature geothermal resources (water-dominated resources) can be effectively achieved using a binary ORC technology. Low-temperature geothermal ORC technology has virtually no GHG emissions to the atmosphere (DiPippo, 2008; Hettiarachchi et al. , 2007) and is an attractive energy-conversion technology due to its simplicity and its limited number of components, all of them being very common and commercially available. Nowadays, the ORC can be considered asthe only proved technology that is commonly used in ranges of afew kW up to 1 MW (Schuster et al. , 2009). Despite the fact that ORC technology is currently associated with low conversion efficiencies,new applications of this technology are commonly examined and implementeddue to its possibility to utilize the low-grade heat from sources, such as low-temperature geothermal resources, for power generation (Ismail, 2011a). A number of successful & innovative ORC binary power plants were installed in different locations (e. g. remote and rural sites) worldwide which demonstrate the ability of this promising alternative technology to utilize renewable low-temperature geothermal energy sources for generating electricity. For example, two plants were installed in Nevada, USA in 1984 and 1987 with electric power generation capacity of 750 and 800 kWe, respectively (Chandrasekharam& Bundschuh, 2008). The production wells supply geo-fluid (water) temperature at 104 oC with a flow rate of 60 l/s to these plants. The ORC binary fluid used was initially R-114 but due to non-availability of this working fluid the plant switched to iso-pentane in 1998. In another location near Empire, Nevada, approximately four 1 MWe units were installed and commissioned in 1987. Two geothermal production wells with geo-fluids temperature of 137 oC were used (Chandrasekharam& Bundschuh, 2008). [SEP] Justify:

Output: The text corroborates the claim by discussing the use of low-temperature geothermal resources for electrical power generation. It mentions the generation of electricity from these resources, specifically highlighting technologies such as binary ORC (Organic Rankine Cycle) that utilize geothermal heat. The text states that innovative applications are being examined for utilizing low-grade heat from geothermal sources, thereby directly supporting the claim of harnessing heat from beneath the Earth’s surface for power generation.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: Different clusters were distinguished and separated showing a significant difference in microbiome diversity (p = 0. 001) between different locations. The samples of animals from location L1 were regrouped together and separated from the other groups while samples of animals from locations L2 and L4 were clustered closer. Fig. 2Microbiome diversity analysis of fecal samples of captive from different locations. Beta diversity using Analysis (PCoA) plots based on the distance showed distinct clusters of fecal microbiome diversity of animals from different locations. P value ≤ 0. 05 was considered statistically significantFull size imageMicrobiome compositionAt the phylum level, the fecal microbiome of all animals was dominated by Bacillota (previously called Firmicutes) and Bacteroidota (previously Bacteroidetes) (Fig. 3A). Bacillota was the higher of the two in the fecal microbiome of animals from location L1. Spirochaetota (previously Spirochaetes) presented higher in the fecal microbiome of animals from location L3. Actinobacteriota (previously Actinobacteria) was less abundant in the fecal microbiome of animals from L2 and L4. Pseudomonadota (previously Proteobacteria) was detected less often, but in all groups, and mainly in L2. Fig. 3Relative abundance of bacterial populations at the phylum (A) and family (B) level in fecal samples of captive from different locations. Taxa on the family level with a relative abundance of less than 3% are classified as “Others”Full size imageAt the taxonomic family level (Fig. 3B), Lachnospiraceae was highly abundant family in the fecal microbiome of animals from all four locations (from 11. 74 to 22. 33%). Lactobacillaceae (17. 09%) was the most dominant bacterial family in the fecal microbiome of animals from location L1, in other locations, the representation was below 1%. Notably, the relative abundance of families Streptococcaceae (7. 84%), Leuconostocaceae (4. 24%), and Peptostreptococcaceae (2. 73%) was presented also higher in the fecal microbiome of animals from location L1 in comparison to animals from other locations. [SEP] Justify:

Output: The text contrasts the claim by presenting findings that demonstrate significant differences in microbiome diversity between animals from different locations. It states, 'different clusters were distinguished and separated showing a significant difference in microbiome diversity (p = 0. 001) between different locations,' which directly opposes the idea that everyone's microbiome composition is identical.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: In the second day, the brains were rinsed and washed twice with PAT3 solution (0. 5% Triton X-100 in 10mM PBS with 0. 5% BSA), each for 1 hour. Then brains were incubated in the blocking and permeabilization solution (3% NGS in PAT3) for 2 hours at room temperature. Incubation of primary antibodies was done overnight at 4°C. On the third day, brains were rinsed and washed twice with PBT solution, then incubated in the secondary antibodies for five days. Both the primary and secondary antibodies were diluted in the PBTN solution. In the staining of GFP-tagged D2R, GFP antibody (Rabbit, ThermoFisher Scientific, Cat. No. A6455, 1: 1000), TH antibody (Mouse, Immunostar, Cat. No. 22941, 1:1000), and mCherry antibody (Rat, ThermoFisher Scientific, Cat. No. M11217, 1:1000) were used. For staining of antibody (Mouse, ThermoFisher Scientific, Cat. No. G6539, 1:100) was used. Goat anti-rabbit with green fluorescence (Invitrogen, 488 conjugate, Cat. No. A-11035, 1:1000), goat anti-mouse with green fluorescence (488 conjugate, Cat. No. A11029, 1:1000), goat anti-mouse with far-red fluorescence (633 conjugate, Cat. No. A21052, 1:500), and goat anti-rat with red fluorescence (546 conjugate, Cat. No. A-11081, 1:1000) secondary antibodies were used. In the seventh day, brains were rinsed and washed twice with PBT solution, and then transferred and mounted in the Fluoro-Gel with on a piece of micro cover glasses. Finally, the samples were covered with another piece of micro cover glasses. Confocal imagingAll images were obtained with a 510 (LSM510, Carl Zeiss, Inc. , USA). Under 40× and 100× objective magnifications, images were collapsed from confocal stacks of 1. 0 μm optical slices. Under 25× objective magnifications, images were collapsed from confocal stacks of 2. 0 μm optical slices. [SEP] Justify:

Output: The text describes a detailed methodology for brain staining and imaging but does not provide any information about olfactory receptors or quantum effects. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: In 1998, a third well with geo-fluid temperature of 152 oC was drilled to maintain the capacity of the plant at approximately 4 MWe. The modular approach was used so that high plant availability factors of 98% and more were achievable (Hammons, 2004). In 1987, another plant was installed and commissioned in Taiwan with an electric power generation of 300 kWe. The plant draws geo-fluids from a 500 m deep well at a temperature of 130 oC. It was reported that the power generated from this facility was sold to the national power grid at 0. 04 US$/kWh (Chandrasekharam& Bundschuh, 2008). In 1986, a low-temperature geothermal ORC unit (Mulka plant) with a power capacity of 15 kWe was commissioned in Australia. The unit was coupled to a geothermal production well which was drilled down toa depth of 1,300 m, and supplying geo-fluid at 86 oC. The unit was operated non-stop for about three and a half years, showing frequency stability and response to load changes (Rosca et al. , 2010). In 1992, a binary ORC power generation unit which utilized a low-temperature geothermal water resource with a temperature ranging from 90 to 115 oC was tested at a location near arderello, Italy. The geothermal power plant generated between 800 and 1,300 kWe of electricity (Rosca et al. , 2010). In Germany, the first low-temperature geothermal power plant using ORC technology was installed at Neustadt-Glewe, with a power capacity of approximately 230 kWe using a geo-fluid temperature of 98 oC (RuggeroBertani, 2007). Another plant was commissioned in Thailand in 1989, with an installed capacity of 300 kWe. The actual production was reported to vary from 150 to 250 kWe and the geo-fluid temperature is 116 oC with a flow rate of approximately 8 l/s (Chandrasekharam & Bundschuh, 2008). In Japan, binary ORC technology was experimentally operated for 5 years starting in 1993 by NEDO (Yamada & Oyama, 2004). [SEP] Justify:

Output: The text corroborates the claim by detailing various geothermal power plants that utilize geo-fluids extracted from beneath the Earth's surface at different temperatures for electricity generation. It provides specific examples, such as the plant in Taiwan drawing geo-fluids from a 500 m deep well with a temperature of 130 °C, and another plant with a temperature of 90 to 115 °C, illustrating how geothermal energy is harnessed for power generation.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: Prevotellaceae presented higher in the fecal microbiome of animals from locations L2 and L4 at percentages of 14. 67% and 13. 67% respectively. Ruminococcaceae (7. 23%) and Spirochaetaceae (7. 60%) both presented higher in the fecal microbiome of animals from location L3. Microbiome composition at the phylum and family levels according to the animal samples are presented in Additional files 2 and 3: Figs. S1A and S1B. The linear discriminant analysis with effect size (LefSe) was used to detect bacterial families (biomarkers) with significant differential relative abundances in fecal microbiome of animals at different locations (Fig. 4). Five bacterial families were detected as biomarkers in the gut microbiome of animals from location L1. Two bacterial families in the fecal microbiome of animals from location L2 and L4. Only one biomarker was identified in the fecal microbiome of animals from location L3. Fig. 4Linear discriminant analysis effect size (LEfSe) of taxa at taxonomic family level in fecal bacterial community of captive from different locations with alpha values of 0. 05 and a threshold value of 2. 0Full size imageQuantitative occurrence of cultured commensal groupsNon-selective and selective media were used to cultivate commensal groups of bacteria in FS of collected from four locations in the with various captive conditions (Fig. 5). Average total counts of anaerobic and facultative anaerobic bacteria in FS of all anteater hosts ranged from 8. 60 to 9. 29 log CFU g−1. Southern Tamanduas’ different captive conditions correlated with various representations of detected cultivable bacterial groups. In general, total anaerobes were significantly higher for location L1 compared to L4. An equally significant trend was also detected for bacterial counts on WSP-MUP for L1 (7. 86 ± 0. 32 log CFU g−1) and L4 (7. 06 ± 0. 66 log CFU g−1). Enrichment of MUP-WSP agar with two different concentrations of norfloxacin (100 mg L−1 and 200 mg L−1) allowed for the detection of different numbers of target bacteria. Counts for L3 (5. 78 ± 0. [SEP] Justify:

Output: The text contrasts the claim by presenting evidence that microbiome compositions vary significantly among animals from different locations, as indicated by the varying percentages of bacterial families like Prevotellaceae, Ruminococcaceae, and Spirochaetaceae. This variability demonstrates that microbiome compositions are not identical among individuals.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: Under 10× objective magnifications, images were collapsed from confocal stacks of 12. 5 μm optical slices. ImageJ software was used to remove other signals outside of the mushroom bodies, as the background noise in GRASP is strong. Larval olfactory learning assaysA single odor learning paradigm was slightly modified from previous publication17,18. In brief, 25 to 50 third-instar larvae (92–96 h after egg laying) were trained on a 2. 5% agar plate (100mm petri dish) covered with 2 mL of 1 M sucrose solution (SUC, Sigma, Cat. No. S1888) or 0. 1% quinine hemisulfate solution (QUI, Sigma, Cat. No. 22640). Distilled water (DW) was used as a control. An odorant pentyl acetate (PA, 10μL, Sigma-Aldrich, CAT. No. 109584) was placed on a small piece of filter inside the lid. After 30 minutes, larvae were rinsed and transferred to the middle line of a new 2. 5% agar plate. A small piece of filter paper with 2. 5μL pentyl acetate was placed on one side of the plate, while distilled water on the other side. After 5 min, the numbers of larvae in the two semicircular areas were counted and the response index (R. I. ) was calculated with the following equation (Figure 2g): Naïve Olfactory TestLarvae were transferred into the midline of test plates. 2. 5μL of odorant were added on one side and distilled water on the other side. The number of larvae in two semicircular areas were counted and the R. I. was calculated after 5 min. Naïve Gustatory TestA petri dish with a median separator was used. Both sides were filled with 1% agar, with 2 mL of distilled water on the control side, and with 1 M sucrose (SUC) solution, or 0. 1% quinine hemisulfate (QUI) solution on the test side. Twenty larvae were put on each side near the midline and allowed to move for 5 min. Gustatory R. I. was calculated using the larvae numbers on two sides90. Larval locomotion assayIndividual larvae were placed on the surface of a plate of 2. [SEP] Justify:

Output: The text does not address the claim regarding olfactory receptors and quantum effects. Instead, it provides procedural details about olfactory and gustatory learning assays in larvae, which are unrelated to the possibility of quantum effects in olfactory receptors.


Input: Task: corroborate the claim using the given text. Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: More recently, in 2006, the first binary ORC plant which utilizes a low-temperature geothermal resource at a temperature of 74oC reported by (RuggeroBertani, 2007) to be the lowest low-temperature geothermal energy resource worldwide) was installed at Springs, Alaska, with a power generation capacity of 200 kWe. A photograph of Chena ORC-based geothermal power plant is shown in Figure 1. A second ORC unit was added, reaching the total installed capacity of 400 kWe net. The total project cost of this binary geothermal plant was $2. 2 million with a simple payback period of 4 years (Holdmann, 2007). In Altheim, Austria, a geo-fluid of temperature 106 oC is utilized both for district heating and electric power generation using a binary plant technology. The net electric output of this plant is 500 kWe, selling to the electric grid 1. 1 GWh in 2006 (RuggeroBertani, 2007). Figure 1. Photograph of Chena ORC-based geothermal power plantat Chena, Alaska, USA (Holdmann, 2007). 2. 2. Energy conversion and performance aspects of ORC-based low-temperature geothermal power generation The ORC is a thermodynamic Rankine cycle that uses an organic working fluid instead of steam (water). A schematic diagram showing a low-temperature geothermal ORC binary-fluid system used for electric power generation is shown in Figure 2. In this system, the first (primary) fluid being the geo-fluid (brine) is extracted from the low-temperature geothermal resource through the production well. The geo-fluid carries the heat from the liquid-dominated resource (thus called the geo-fluid heat carrier) and efficiently transfers this heat to the low-boiling point (BP) organic working fluid (the secondary fluid) using an effective heat exchanger; shell-and-tube heat exchangers arewidely used (Chandrasekharam& Bundschuh, 2008). In this binary-fluid system, the low-boiling point organic liquid absorbs the heat which is transferred by the geothermal fluid and boils at a relatively much lower temperature (compared to water) and as a result develops significant vapor pressure sufficient to drive the axial flow or radial inflow turbine. [SEP] Justify:

Output: The text corroborates the claim by providing detailed information about binary ORC (Organic Rankine Cycle) plants, which are designed for low-temperature geothermal resources. It explains how these systems extract geo-fluid (brine) from geothermal wells, highlighting the process of transferring heat from the Earth to an organic working fluid for electric power generation. This directly supports the claim that geothermal energy harnesses heat from beneath the Earth’s surface.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: 32 log CFU g−1) and L1 (5. 71 ± 1. 06 log CFU g−1) on WSP-NORF 1 were significantly higher compared to counts for L4 (4. 20 ± 0. 34 log CFU g−1), while counts on WSP-NORF 2 were significantly higher for L3 (6. 23 ± 0. 55 log CFU g−1) in comparison with all other monitored locations. Lactic acid bacteria on Rogosa agar were significantly higher in L1 (8. 52 ± 0. 95 log CFU g−1) compared to other locations, and in L2 (7. 18 ± 0. 66 log CFU g−1) in comparison with L4 (5. 62 ± 0. 72 log CFU g−1). Then, E. coli counts (blue colonies with β-glucuronidase activity) were higher in L2 (8. 44 ± 0. 22 log CFU g−1) compared to L1 (7. 06 ± 0. 94 log CFU g−1) and L4 (5. 93 ± 0. 63 log CFU g−1), higher were also in L3 (8. 19 ± 0. 59 log CFU g−1) compared to L4. Interestingly, the counts of remaining coliforms (white colonies) proved to be significantly higher in L1 (8. 24 ± 0. 53 log CFU g−1) compared to L3 (6. 69 ± 0. 86 log CFU g−1). Fig. 5Cultivation counts of monitored bacterial groupsFull size imageCultivable commensal bacterial groups in feces of Southern TamanduasMore than one thousand grown isolates (n = 1078) were analyzed, and 92. 58% of these isolates were successfully identified using MALDI-TOF MS at the species level, and 80 selected isolates were determined as unidentified. In total, 63 bacterial species (Additional file 4: Table S2A) were isolated and identified on the used media designed for total anaerobes (WSP agar), bifidobacteria/clostridia (WSP--NORF 1, WSP-NOR 2 agars), lactic acid bacteria (Rogosa agar) and coliforms, as well as E. [SEP] Justify:

Output: The text contrasts the claim by providing detailed data on the composition of bacterial groups found in different locations, indicating significant variability in counts of specific microbial populations. For instance, it states that counts of lactic acid bacteria and E. coli were significantly higher in certain locations compared to others, demonstrating that microbiome compositions differ across individuals or environments.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: 5% agar mixed with 1mL India ink. They were allowed to acclimate for 1 min, and then a video was recorded for 30 seconds using a Moticam3 digital camera (Motic) and Plus 2. 0 software. The video was analyzed by the MTrack2 plug-in (from in ImageJ. The path was recorded; scores were quantified as the length traveled per minute as previously described91. As the locomotion speed of DAN-c1 homozygous was slow, DAN-c1 × WT was used as the control group. Learning assays with thermogeneticsIn learning assays with thermogenetics, 25 to 50 third-instar larvae (92–96 h after egg laying) were trained on a 2. 5% agar plate (100mm petri dish) covered with 2 mL of 1 M SUC or 0. 1% QUI. DW was used as a control. An odorant PA was placed on a small piece of filter inside the lid. Training plates were put in a water bath either under 22°C or 34°C. After 30 minutes, larvae were rinsed and transferred to the testing plate. After 5 min, the response index (R. I. ) was calculated. Learning assays with optogeneticsIn learning assays with optogenetics, egg laying plates with 1mM ATR (all-trans retinal, Sigma, Cat. No. R2500) were used. All-trans retinal (ATR) is a necessary light-isomerizable chromophore for ChR2, which is not synthesized by Drosophila. 92,93 Around 50 third-instar larvae were trained in a 35mm petri dish with 2 mL of either 1 M SUC or 0. 1% QH solutions. DW was used as a control. During training, an odorant was placed on a small piece of filter inside the lid. To activate channelrhodopsin2, a LED (07040 PB000-D, wavelength 470 nm) with a power supply (power supply Model GPS-1830D) was used. The intensity of the blue light was 25 mW, measured by a laser power meter (Sanwa, LP1). After being trained for 30 minutes, larvae were rinsed and transferred to the middle line of a 2. 5% agar plate in 100 mm test plate. [SEP] Justify:

Output: The text discusses experimental procedures involving larvae and various substances, but it does not address or provide any information regarding olfactory receptors or their potential quantum effects. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: The turbine is coupled to an electric generator which converts the turbinemechanical shaft power into electrical power. The organic working fluid expands across theturbine and then is cooled and condensed in thecondenser before it is pumped back as a liquid to the heat exchanger using a condensate Figure 2. A schematic diagram showing the basic concept of a low-temperature geothermal binary ORC system for electrical power generation. pump to be re-evaporated, and the power cycle repeats itself. One of the most important performance criteria in low-temperature geothermal ORC power generation technology requires the optimal selection of the ORC organic working fluid. Organic fluids used in binary ORC technology have inherent feature (compared to water) and that is they have low boiling temperature and high vapor pressure at relatively low temperatures, compared with steam (water) (Dickson & Fanelli, 2005). Typical ORC organic fluids may include pure hydrocarbons (e. g. pentane, butane, propane, etc), refrigerants (e. g. R134a, R218, R123, R113, R125, etc), or organic mixtures (Panea et al. , 2010; Saleh et al. , 2007; Hung, 2001; Wei et al. , 2007). The optimal energy conversion performance of a low-temperature geothermal ORC power generation system depends mainly on the type of organic fluid being used in the system (Ismail, 2011a). The selection of the type of organic fluid is normally based on the following criteria (Hettiarachchi et al. ,2007; Saleh et al. , 2007; Chandrasekharam& Bundschuh, 2008; Ismail, 2011b): The ORC organic fluid should be environmentally friendly; less in ozone depletion potential (ODP) and global warming potential (GWP). It should result in high thermal efficiency by allowing maximum utilization of the available low-temperature geothermal heat source. It should be safe (non-flammable and no-toxic) and non-corrosive. It should have a low-boiling temperature and should evaporate at atmospheric pressure. It should lead to optimum design and cost effectiveness of the ORC system. It should not react or disassociate at the pressures and temperatures at which it is used. It should have suitable thermal stability and high thermal conductivity. [SEP] Justify:

Output: The text corroborates the claim by discussing the process of converting geothermal energy into electrical power through a low-temperature geothermal organic Rankine cycle (ORC) system. It mentions how the system utilizes geothermal heat to operate a turbine coupled to an electric generator, thus confirming the claim that geothermal energy is harnessed for power generation.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: coli with β-glucoronidase activity (TBX agar). Each detected species was identified with a high degree of certainty with species consistency using MALDI-TOF MS. The most bacterial species were detected in animals from locations L1 and L2 (both, n = 35), L4 (n = 31), and least in L3 (n = 27). Table 2 presents the most frequently detected species (n = 32), selected from all detected species on the assumption that their occurrence was detected in two individual animals from two different locations. Moreover, Citrobacter freundii, Cb. youngae, Clostridium baratii, C. colicanis, C. perfringens, Enterobacter cloacae, Eb. hormaechei, Enterococcus hirae, Escherichia coli, Pediococcus pentosaceus, and Streptococcus lutetiensis were detected in feces of all animals. Also, orange-pigmented colonies of cocci identified as Lactococcus garvieae were frequently detected. The selective media supplemented with mupirocin and acetic acid, as well as with added norfloxacin allowed for mainly clostridial isolation. When C. baratii, C. colicanis, and C. perfringens were repeatedly detected in the FS of from all locations. sordellii and Paraclostridium bifermentans were detected in animals from locations L1, L3, L4 (all zoos), but not in those from the private breeder (L2). The detection of bifidobacteria was rather random or rare. animalis was detected in multiple locations (L1 and L2; Table 2). Furthermore, B. anseris and B. asteroides (both, L4) were detected, and B. pseudolongum in FS of animals from location L1. Thus, the detected numbers on these media are more related to the quantification of viable culturable CFU of clostridia. [SEP] Justify:

Output: The text contrasts the claim by demonstrating the variability in microbiome composition among different animals in various locations, as it describes the presence of multiple bacterial species detected in the feces of animals from diverse locations (L1, L2, L3, and L4) and highlights that certain species were not found in some locations ('sordellii and Paraclostridium bifermentans were detected in animals from locations L1, L3, L4...but not in those from the private breeder (L2)'). This indicates that microbiome compositions are not identical across all individuals or locations.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: A small piece of filter paper with pentyl acetate was placed on one side of the plate, while distilled water on the other side. Then the number of larvae in the two semicircular areas were counted and the R. I. was calculated after 5 min. Quantification of D2R knockdownQuantification of the fluorescent intensity of D2R knockdown was performed as follows. TH signals were used to define dopaminergic neurons, and the mean fluorescent intensity of GFP in each neuron was calculated with subtraction of the background. The mean intensity of DM1 was divided by that of pPAM, and the value in the knockdown group was subsequently normalized with the control group. Statistical AnalysisInformation for statistical analysis is provided in figure legends. Author contributionsQi. C. : Conceptualization, Methodology, Formal analysis, Investigation, Writing – Original Draft, Visualization, Qian. C. : Writing – Review & Editing, Steijvers. E. : Writing – Review & Editing Colvin. R. : Writing – Review & Editing Lee. D. : Conceptualization, Writing – Review & Editing, Supervision, Funding acquisitionAcknowledgementsThis work was partially supported by an NIH grant (AG065925) and an Grant from of Science & Technology (Institute), Seoul, Korea. CQ was a recipient of the SEA and GSR awards from Ohio University. We thank Dr. J Hirsh (University of Virginia), Dr. M. Wu (University), Dr. M. Zlatic and Dr. C. Eschbach (), Dr. M. Gallio (Northwestern University), Dr. A. Kopin (Tufts-Medical Center), Dr. S. Tanda (Ohio University), Dr. B. Condron (University of Virginia), Dr. T. Kitamoto (University of Iowa) for their kind gift strains. Declaration of InterestThe authors declare no competing interests. Supplemental informationFigure S1. GFP expression patterns in the larval CNS by GAL4 driver strains used in this study. (a-n) Representative pictures show the patterns of distinct GAL4 driver strains crossed with a UAS-GFP strain. (o) A representative picture shows the pattern of MB247-LexA driver (MB247-LexA::VP16) crossed with a LexAop-RFP strain (LexAop-rCD2::RFP). [SEP] Justify:

Output: The text is irrelevant to the claim as it does not mention olfactory receptors or quantum effects. Instead, it focuses on experimental methods involving larvae and statistical analysis, which do not support or refute the claim about olfactory receptors.


Input: Task: corroborate the claim using the given text. Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: 036 E3 For example, using Eq. (3) it can be estimated that a thermal efficiency of approximately 4. 8% could be achieved for power generation with a geo-fluid extracted from a low-temperature geothermal resource available at 130 oC. The thermal efficiency as a function of the geothermal heat resource temperature, T g e o i n (in K), and ambient temperature, T o (in K) is given by (DiPippo, 2007) η t h ≅ 0. 58 T g e o i n - T o T g e o i n + T o E4 So for example, with a geothermal heat resource temperature of 130oC and ambient temperature of 25oC, the thermal efficiency is estimated to be 8. 7%, using Eq. (4). It should be noted that Eq. (4) is valid for resource temperatures between 100 and 140 oC. The estimated net power output produced by the geothermal power system can also be determined using (DiPippo, 2007) W ˙ o u t ≅ 2. 47 m ˙ g e o T g e o i n - T o T g e o i n + T o T g e o i n - T s i n k E5 In Eq. (5), m ˙ g e o is the geo-fluid mass flow rate; and T s i n k is the heat sink temperature. It should be noted that the above correlations given by Eqs. (2) through (5) provide quick estimate of the thermal efficiency and net power output. However, for more accurate system performance predictions, a detailed energy analysis should be performed to predict the net power, the available geothermal heat, and overall thermal efficiency using Eq. (1). Since the geothermal energy is produced at low enthalpy levels,ORC-based low-temperature geothermal power generation plants tend to have low thermal efficiencies: 10-13% reported by (DiPippo, 2007), 2. 8-5. 5% reported by (Gupta & Roy, 2007), and 5-9% reported by (Hettiarachchi et al. , 2007). [SEP] Justify:

Output: The text corroborates the claim by discussing the use of geothermal resources, specifically mentioning the extraction of geo-fluids from the Earth's interior to generate power. It provides information regarding thermal efficiencies and net power output from geothermal energy systems, aligning with the claim that geothermal energy harnesses heat from beneath the Earth's surface for power generation.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: Table 2 The most frequently detected bacterial species of by cultivation on selected media (presented species occurred in at least two animals from two different locations)Full size tableThe elective agar (WSP) as well as selective media used for cultivation of bifidobacteria/clostridia also allowed for the growth of enterococci, pediococci, streptococci, and other bacteria (Additional file 4: Table S2B). Detection of lactobacilli was paradoxically more frequent on these media than on Rogosa agar, where Pc. pentosaceus dominated, and frequently occurred Weissella paramesenteroides (Additional file 4: Table S2C). On the TBX medium, it was mainly the genera such as Escherichia, Enterobacter, Enterococcus, Citrobacter, Klebsiella that were detected, along with some bacteria that were not coliforms e. g. Lc. garvieae, Pc. pentosaceus, Strep. lutetiensis, and others less frequently occurred. E. coli with β-glucoronidase activity were detected in FS of all Southern Tamanduas, but also white colonies of E. coli were detected in nine out of the eleven animals (Additional file 4: Table 2D). Some species were detected based on location. These were, for example, species such as Enterococcus casseliflavus, Hungateli hathewayi, Phocaeicola massiliensis, P. vulgatus, Prevotella copri, Raoultella ornithinolytica, R. planticola, Secundilactobacillus malefermentans, Staphylococcus capitis, and S. warneri that were detected only with the private breeder (L2), then Sphingobacterium thalpophilum, Veillonella dispar, V. ratti, and Weissella cibaria (L1), W. confusa (L4), and Acinetobacter lwoffii (L3). On the other hand, Actinomyces urogenitalis was also detected in animals from three locations (L2, L3, L4). [SEP] Justify:

Output: The text contrasts the claim by providing specific examples of different bacterial species detected in various animals from different locations. It highlights the variability in microbiome composition indicated by the detection of species that occurred only in certain locations, suggesting that microbiomes are not identical among different animals and locations.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: Blue channel represents neuropils marked by nc82 antibody. Driver strains in (a-j) were used in Figure 1d-m. Driver strains in (k-m) are strains used in supplementary Figure S3. 201Y-Gal4 (N) is the driver strain used in Figure 6. Scale bar: 200 µm. Figure S2. Controls for GRASP experiments. (a-c) signals were not observed in control groups. The first column shows the mouse anti-GFP staining (green) for GRASP signals, the second column shows MB lobes by RFP (red), and the third column shows the rabbit anti-GFP staining (blue) which only recognizes the spGFP1-10. (a) (mouse antibody, green) and spGFP1-10 (rabbit antibody, blue) can be recognized in the lower peduncle (LP) compartment (white arrows), in a larval brain expressing spGFP1-10 under TH-Gal4 and spGFP11 under MB247-LexA. Some strong spGFP1-10 signals outside of MB are also colocalized with GRASP signals (yellow arrowheads). (b) GRASP signals are hardly observed in a larval brain only expressing spGFP1-10 under TH-Gal4 (no MB247-LexA in this brain), while anti-spGFP1-10 signals are still strong (magenta arrows). (c) nor spGFP1-10 can be recognized in a larval brain only expressing spGFP11 under MB247-LexA (cyan arrowheads). Scale bars: 20 µm. (d) A Schematic diagram shows the mechanism of GRASP. Modified from Macpherson et. al. 89. Figure S3. D2R-GAL4 strains support the expression pattern of D2R. (a-b) Control staining for D2R-tagged GFP in Figure 3. The green channel represents GFP signals whereas magenta represents neuropils marked by nc82 antibody. GFP staining in WT (a). Secondary antibody only staining for the D2R-tagged GFP strain (b). [SEP] Justify:

Output: The text does not provide any information related to olfactory receptors or quantum effects. Instead, it discusses various aspects of neuroanatomy and experimental setups related to larval brain studies involving staining techniques and driver strains, which are irrelevant to the claim about olfactory receptors.


Input: Task: corroborate the claim using the given text. Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: Maximizing generating power capacity is normally sought from these power plants by maximizing the geo-fluid flow rate (depending on the capability of the production well) with a limited geo-fluid temperature available from the geothermal resource. It was reported (Chandrasekharam& Bundschuh, 2008) that low-temperature geothermal production wells with geo-fluid temperature < 150 oC and geo-fluid flow rate > 900 l/min could generate electric power ranging from 50 to 700 kWe. When appropriate, multiple production wells could be installed using the same low-temperature geothermal energy reservoir so that a number of ORC power generation units could be cascaded to obtain larger power production rates from the plant (Gupta & Roy, 2007). Limited by the second-law of thermodynamics, the ideal (absolute maximum) efficiency of a thermoelectric power cycle, such as the low-temperature geothermal ORC power cycle, operating as a reversible heat engine between a heat source at a temperature T H and a heat sink at a temperature T L is Carnot efficiency, given as (Cengel& Boles, 2008) η i d e a l = η C a r n o t = 1 - T L T H E6 For example, for an ORC power system using a geo-fluid extracted from a low-temperature geothermal heat source at 130 oC (403 K) and a heat sink (condenser) at 40 oC (313 K), the maximum ideal Carnot efficiency can be calculated using Eq. (6) to be approximately 22. 3%. For an actual (irreversible) ORC-based geothermalsystem operating between the same temperature limits would have lower efficiency. Another measure of the performance of the low-temperature geothermal ORC power plant can be obtained using the Second-Law of thermodynamics in the form of exergetic efficiency, η e x given as η e x = W ˙ o u t E x ˙ g e o E7 The exergetic efficiency in Eq. (7) is defined as the ratio of the actual net power output from the power generation system to the maximum theoretical power that could be extracted from the geo-fluid at the geothermal resource state relative to the thermodynamic dead-state. [SEP] Justify:

Output: The text corroborates the claim by discussing the process of generating electric power from low-temperature geothermal resources, which involves extracting geo-fluid from beneath the Earth's surface and utilizing its heat. It details how production wells can be used in geothermal power plants to harness this heat, aligning with the claim that geothermal energy is derived from the Earth's heat for power generation.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: DiscussionFecal microbiome of captive myrmecophagous represented by Southern TamanduasMicrobiome studies on several animal species were performed during the last decade through the rapid development of DNA sequencing methods and tools. This advance makes it possible to analyze hundreds of samples from different animal species simultaneously to obtain a general overview of their microbiome. However, there is still uncertainty as to the variability of the microbiome of different animal orders and whether certain bacteria within a species are subject to greater fluctuations than others [25]. The first research addressing the microbiome of myrmecophages was published by Delsuc et al. [2], who reveal specialized placental myrmecophages as a spectacular case of large-scale convergence in gut microbiome composition. Later, the study of de Jonge et al. [12] described similarities and differences in the gut microbiome composition in 54 animal specimens across 42 species, including the Giant Anteater. Using non-metric, multi-dimensional scaling analysis based on Bray–Curtis distances, the primarily herbivoric orders Perissodactyla, Proboscidae, Diprodontia, Artiodactyla, and Pilosa were somewhat clustered together, while Carnivora, Rodentia, Lagomorpha, and Primates were grouped separately. The highest richness in alpha diversity was seen in the order Pilosa, represented by the in comparison with other captive animals. Here we present a dataset that includes the fecal microbiome of captive from varying breeding and diet conditions. The fecal microbiome of analyzed captive animals was dominated by the phyla Bacillota (Firmicutes) and Bacteroidota (Bacteroidetes). Pseudomonadota (Proteobacteria), Spirochaetota (Spirochaetes), and Actinobacteriota (Actinobacteria) were less abundant, and their abundance was more varied based on the location and animal. Similar results to the phyla results were presented by Delsuc et al. [2]. At the taxonomic family level, and Peptostreptococcaceae were represented in the fecal microbiome of animals from all locations. Lactobacillaceae dominated in L1. Other locations yielded low abundance or no representation at all. On the other hand, the absence and high representation of Lactobacillaceae may be primarily related to diet. [SEP] Justify:

Output: The text contrasts the claim by discussing the variability in the fecal microbiome composition among different animal species and highlighting how certain bacteria within a species can exhibit significant fluctuations. It states that studies have shown variability in microbiome composition based on breeding and diet conditions, which implies that microbiomes are not identical across individuals.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: (c-e) D2R-GAL4 strains support the expression of D2R in some DANs. The green channel represents GFP signals, red represents mCherry signals under D2R-GAL4 drivers, and blue marks DANs with TH antibodies. R72C08 labels three DM1 neurons (c). R72C04 labels one DM1 (d) and two DL2b neurons (e). (f-h) D2R-GAL4 strains support the expression of D2R in mushroom body neurons. The green channel represents GFP signals, and red represents mCherry signals under D2R-GAL4 drivers. R72D03 marks some MBNs in mushroom body (f). R72C08 labels some MBNs in axons (g), dendrites and soma (h). (i) D2R is absent in the core of mushroom body lobes, from a transection view of the lower peduncle. Scale bars: 200 µm (a and b); 20 µm (c-e, g-i), 50 µm (f). Figure S4. D2Rs in DAN-d1 and DAN-g1 are not necessary for aversive learning. (a-b) Dendrites and axons of DAN-d1 (a) and g1 (b) are labeled by DenMark (red) and sytGFP (green), correspondingly. (c-d) D2Rs are expressed in DAN-d1 (c) and DAN-g1 (d). The expression pattern of D2R is shown with tagged--g1 and d1 are marked by mCherry, and DANs are labeled by TH-antibody (blue). (e) Knockdown D2R in neither in DAN-g1 nor DAN-d1 impairs aversive learning. Data are shown as mean ± SEM. Two-way multiple comparisons test, **p < 0. 01, ***p < 0. 001, ****p < 0. 0001. numbers, see Table S3. (f) The gene structure of D2R, the insertion site of GFP, and the D2R-microRNA targeting sequence are shown in a schematic diagram. Modified from Xie and Ho61. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the expression of D2 receptors (D2R) in certain neurons and their role in aversive learning, without addressing the functionality or mechanisms of olfactory receptors or any mention of quantum effects.


Input: Task: corroborate the claim using the given text. Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: This involves determining the rate of exergy carried by the geo-fluid to the ORC power system. Typically, the design and operation of geothermal binary power generation systems should be optimized in order to increase their thermal and exergetic efficiencies guided by the Carnot efficiency (Ismail, 2011b). 2. 3. ORC-based low-temperature geothermal power generation: Environmental & economic aspects Geothermal power generation is relatively pollution-free and considered to be a clean technology for power generation (Dickson & Fanelli, 2005) and it tends to have the largest technological potential compared to other renewable energy sources used for power generation (Hammons, 2004). Once up and running, GHG emissions are typically zero when low-temperature geothermal energy reservoirs are utilized using ORC power systems, since all of the produced geo-fluid is injected back into the reservoir (Hammons, 2004). In this case, one of the effective ways of getting rid of hazardous chemical constituents of geothermal water (e. g. trace metals) is re-injection. ORC-based low-temperature geothermal power generation systems are far less environmentally intrusive than alternative power generation systems in several respects, e. g. they are essentially zero-GHG emission systems and have low land usage per installed megawatt (DiPippo, 2008). As far as physical environmental effects, geothermal projects may cause some kind of disruption activities as other same size and complexity of civil engineering projects. Also, the locations of excavations and sitting of boreholes and roads will have to be taken into account, soil and vegetation erosion, which may cause changes in ecosystems, has to be watched. It should be noted that many geothermal installations are in remote areas where the natural level of noise is low and any additional noise is very noticeable (Dickson & Fanelli, 2005). There is a relatively larger production of waste-heat energy in geothermal systems, and this needs to be dissipated in an environmentally acceptable way. In ORC-based low-temperature geothermal power systems, the thermal impact is much reduced by disposing of waste geothermal water using deep re-injection approach so that the thermal impact of the waste heat becomes insignificant (Dickson & Fanelli, 2005). [SEP] Justify:

Output: The text corroborates the claim by discussing the mechanism of geothermal energy and its application in power generation, particularly through ORC (Organic Rankine Cycle) systems. It mentions the 'geo-fluid' and 'thermal and exergetic efficiencies,' which are directly related to harnessing heat from beneath the Earth. The emphasis on the 'pollution-free' nature of geothermal power generation and its clean technology aspect further supports the claim that geothermal energy is a viable source for power generation.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: Only animals from location L1 had a zoo-made diet, while others from locations L2–L4 had a complete commercial diet. The presence of Lactobacillaceae taxa in the gut microbiome is highly dependent on the host's diet [26, 27]. The effect of diet and breading conditions on the gut microbiomeStudies examining diverse arrays of animal species and comparing the microbiome of different habitats/groups and species has provided valuable insights [10, 22, 28,29,30,31,32]. We analyzed microbime composition and selected cultivable microbes from 33 FS of 11 anteaters (Tamandua tetradactyla) from 4 locations. The diet in these three locations (L2–L4) was mainly a complete commercial diet and in location L1 a zoo-made diet. This difference can explain the significantly different microbial profile of the L1 animal group, as it had already been described in regard to other animal species and humans [8, 33]. Moreover, the use of probiotic and prebiotic intervention can cause microbial shifts [34, 35]. Namely, fructooligosaccharides and inulin were present in the complete commercial diet, as well as the probiotic strain of Enterococcus faecium E1708. However, species Ec. faecium was also present in other probiotic supplements, therefore, it was supplied to all animals through their diet. A more varied probiotic supplement (Saccharomyces cerevisiae CNCM I-1077, Bacillus licheniformis DSM 5749, Bacillus subtilis DSM 5750, and Enterococcus faecium NCIMB 10415) was administered to the L1 group, which may explain the differing microbiome profile for example through microbial interaction. Detection of mentioned species through cultivation screening can indicate their transit through the gastrointestinal tract of anteaters. However, we are not able to distinguish whether these were the administered probiotic strains or the original strains of Southern Tamanduas. However, to increase the probability of colonization, it is recommended to use a strain originally isolated from the digestive tract of the species for which the given probiotics are intended [36]. In addition, the used insects as feed could potentially be a source of microbes and influence the composition of the fecal microbiome [37]. [SEP] Justify:

Output: The text contrasts the claim by explaining that the composition of the gut microbiome varies significantly based on factors such as the host's diet and location. It highlights how the presence of specific bacterial taxa, such as Lactobacillaceae, is influenced by the diet, indicating that different feeding practices can lead to distinctly different microbiome profiles among animals from various locations, suggesting that microbiome compositions are not identical.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: Scale bars: 50 µm (a and b), 20 µm (c and d). Figure S5. Knockdown D2R in DAN-c1 with a RNAi strain also impairs aversive learning. (a) Knockdown of D2R with D2R-miR in DAN-c1 impairs larval aversive learning when using propionic acid as the odorant. (b) Knockdown of D2R in DAN-c1 with a RNAi strain also impairs larval aversive learning when using pentyl acetate as the odorant, while knockdown of D2R in either DAN-d1 or g1 does not affect learning. (c) Knockdown of D2R with D2R-miR in DANs under TH-GAL4 impairs larval aversive learning when using pentyl acetate as the odorant. Data are shown as mean ± SEM. Two-way multiple comparisons test, *p < 0. 01, **p < 0. 01, ***p < 0. 001, ****p < 0. 0001. numbers, see Table S3. Figure S6. Naïve sensory and motor functions of Drosophila larvae. (a-e) The naïve sensory and motor functions in larvae related to D2R-miR experiments. (a) No significant difference exists between strains in naïve olfactory tests toward pentyl acetate (PA). (b) No significant difference exists between strains in naïve olfactory tests toward propionic acid (ProA). (c) No significant difference exists between strains in naïve gustatory tests toward quinine (QUI). (d) No significant difference exists between strains in naïve gustatory tests toward sucrose (SUC). (e) No significant difference is found between strains and WT, except DAN-c1. So, larvae from DAN-c1 × WT are used for all behavioral assays (refer to i). (f-i) The naïve sensory and motor functions in larvae related to RNAi experiments. (f) No significant difference exists between strains and WT. (g) No significant difference exists between strains in naïve gustatory tests toward QUI. (h) No significant difference exists between strains in naïve gustatory tests toward SUC. [SEP] Justify:

Output: The text discusses various experimental outcomes related to D2R knockdown and aversive learning in Drosophila larvae. However, it does not provide any information supporting or contradicting the claim regarding the function of olfactory receptors through quantum effects. Therefore, it is deemed irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: Appropriate measures should be applied to prevent leakage of the binary working fluid from ORC power generation units to the environment (Yamada & Oyama, 2004); normally the installations of these units are made perfectly tight to meet high safety standards. In theory, geothermal energy potential is present below the entire surface of the Earth. In practice however, special geologic settings are required for geothermal energy to be economically exploited (Grasby et al. , 2011). Generating electricity using ORC-based geothermal technology is very cost-effective and reliable (Chandrasekharam& Bundschuh, 2008; Dickson & Fanelli, 2005). Table 1 compares electrical energy costs produced by various renewable energy technologies. The cost of geothermal energy for generating electricity is favourable compared to other energy sources. The reported costs of low-temperature based small geothermal power plants vary from 0. 05 to 0. 07 US$/kWh for units generating < 5 MWe (Chandrasekharam& Bundschuh, 2008). (US cents/kWh) Cost(US$/kWe) Energy Cost(US cents/kWh) Geothermal 2-10 800 – 3,000 1-8 Wind 5-13 1,100 – 1,700 3-10 Solar photovoltaic 25-125 5,000 – 10,000 5-25 Solar thermal 12-18 3,000 – 4,000 4-10 Biomass 5-15 900 – 3,000 4-10 Tidal 8-15 1,700 – 2,500 8-15 Hydro 2-10 1,000 – 3,000 NA Table 1. Energy and investment costs for electric power production from different renewable energy sources (Hammons, 2004; Dickson & Fanelli, 2005). The unit cost of electricity generated from low-temperature geothermal based small power plants is compared in Table 2. Moreover, the unit cost of electricity from small-scale geothermal plants (<5 MWe) is much lower than the average cost of 0. 25 US$/kWh supplied through diesel generators (Chandrasekharam& Bundschuh, 2008). [SEP] Justify:

Output: The text corroborates the claim by discussing geothermal energy as a source of electricity generation, indicating that it is economically viable when special geological conditions are present. The mention of ORC (Organic Rankine Cycle) technology in geothermal power generation supports the idea that geothermal energy effectively harnesses heat from beneath the Earth's surface for this purpose.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: Just like the diet and other supplements, the presence of another animal species during exposure could potentially be the source of the differing microbiome, especially during longer-term exposure [38]. All anteaters from zoo locations shared exposure with other animal species while animals from the private breeder did not. Animal species-specific responses within the microbiome might play a pivotal role in determining which animals can better adapt to changes brought about by captivity, where analyses of the intestinal microbiome might have a significant role [39]. All fecal samples used in this study were collected from animals in captive conditions. Animals in captivity experience a range of altered conditions compared to their wild counterparts, including changes in diet, social structure, population density, human contact, medical treatment, and antibiotic administration [40]. These changes introduce selective pressures on the animals, affecting their gut microbiome composition, and reducing diversity and functional aspects of the microbiome [10, 41]. These alterations in the gut microbiome can potentially lead to negative effects on the health of the animals [39, 40]. It is essential to deepen our understanding of the effects of captivity on animal microbiomes in order to provide optimal care to create more suitable captive conditions that align with the animal's natural biology and wellbeing, particularly in terms of its health and overall welfare [10, 39, 42, 43]. Species variability and significance of anteater cultivable microbesHigh proportions of bacteria are culturable across major biomes within known techniques [44] when the gut microbiota is an infinite source of microbes and is considered one of the key elements that reflect the health status of the host [45]. Here we focused on well-cultivated commensal microbes to see their species variability across captive anteater hosts. Although the family Clostridiaceae was not among the most represented families, its presence was common for the microbiome of all anteaters. It corresponded with the cultivation results, where clostridia dominated among viable anaerobes on mupirocin and norfloxacin media with relatively stable species representation in comparison with bifidobacteria. Clostridia seem to be naturally resistant to mupirocin and norfloxacin, and low or absent quantitative representation of bifidobacteria in the fecal sample allows their detection [46, 47]. The presence of C. baratii, C. colicanis, C. perfringens, Paenicl. sordellii, and Paracl. [SEP] Justify:

Output: The text contrasts the claim by highlighting the variations in microbiome composition influenced by factors such as diet, species interactions, and conditions of captivity. It suggests that ‘species variability’ and the individual responses within the microbiome demonstrate that microbiome compositions are not identical among different animals or under various conditions. The differences in exposure to other animal species and the altered conditions in captivity indicate that microbiome diversity exists rather than uniformity.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: (i) There is a significant difference between strains in larval locomotion speed, and there is significant difference between DAN-d1, DAN-d1 × RNAi and WT, but these differences do not affect the learning ability of larvae. Data are shown as mean ± SEM. One-way multiple comparisons test. numbers, see Table S3. Figure S7. Over-excitation of DANs during learning impairs larval aversive learning. Third instar larvae with ChR2 expression in most DANs (TH-Gal4) were used. Activation of DANs during training impairs larval aversive learning (a), while keeps appetitive learning intact (c). No learning behaviors are observed in the control distilled water (DW) groups (b). Data are shown as mean ± SEM. Two-way multiple comparisons test, ***p < 0. 001. numbers, see Table S4. Supplementary TablesTable S1. Other strains used in this study. Table S2. N numbers of learning assays with thermogenetics. Table S3. N numbers of DD2R knockdown experiments. Table S4. N numbers of learning assays with optogenetics10. 1016/j. cell. 2014. 03. 0012Neve K. A. Seamans J. K. Trantham-Davidson H. 2004Dopamine receptor signalingJ 24:165–205 J. H2013Dopamine signaling in reward-related behaviorsCircuits 7 C. Nash S. R. Robinson S. W. Jaber M. Caron M. G1998Dopamine receptors: from structure to function78:189–225 A. Dunnett S. B2007Dopamine neuron systems in the brain: an update30:194–202 M. V. Antzoulatos E. G. Miller E. K2014Prefrontal dopamine in associative learning and memoryNeuroscience 282:217–229 M2014The ventral tegmentum and dopamine: A new wave of diversityNeuroscience 282:243–247 R. Benarroch E. E2014Dopamine receptor signaling in the forebrain: recent insights and clinical implicationsNeurology 83:758–767 J. M. Gainetdinov R. R2011The physiology, signaling, and pharmacology of dopamine receptors63:182–217 M. [SEP] Justify:

Output: The text provided does not address the claim regarding olfactory receptors and their potential quantum effects. Instead, it discusses larval locomotion speed, learning ability, and dopamine receptor signaling, which are unrelated topics. Therefore, the text is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: The total investment for a geothermal power plant mainly includes the following types of costs: (1) cost of exploitation, (2) cost of drilling, (3) cost of power plant (capital cost of design and construction), and (4) operating & maintenance costs (Chandrasekharam& Bundschuh, 2008). The first two types are referred to as subsurface costs whereas the other two are referred to surface costs. The high initial investments incurred through the exploration, drilling and development of wells and the production field is an important constraint on future geothermal power development. Despite low maintenance and operational costs, high initial investments are often a strong restrictive(Grasby et al. , 2011). For small-scale geothermal power plants (<5 MWe) utilizing low-temperature resources, the subsurface cost typically accounts for approximately 30% of the total investment costs whereas the surface cost accounts for the remaining 70%. Net Power(kWe) (US$/net kWe) O&M Cost(US$/year) Temperature (oC) 100 120 140 100 2,786 2,429 2,215 21,010 200 2,572 2,242 2,044 27,115 500 2,357 2,055 1,874 33,446 1000 2,143 1,868 1,704 48,400 Table 2. Unit cost of electricity generated from low-temperature based small power plants (Chandrasekharam& Bundschuh, 2008; DiPippo, 2008). Generating electricity using low-temperature geothermal ORC technology is very reliable due to its advanced technological aspects. However, the maintenance costs and shutdowns could be reduced when the technical complexity of the plant is on a level that is accessible to local technical personnel or to experts who are readily available (Dickson & Fanelli, 2005). As mentioned before, geothermal ORC power generation plants are normally constructed and installed in small modular power generation units. These units can then be linked up to create power plants with larger power production rates. Their cost depends on a number of factors, but mainly on the temperature of the geothermal fluid produced, which influences the size of the ORC turbine, heat exchangers and cooling system. [SEP] Justify:

Output: The text corroborates the claim by discussing geothermal energy and its application in power generation, specifically mentioning that geothermal ORC power generation plants are utilized for generating electricity. It also describes how the temperature of the geothermal fluid is a crucial factor influencing the equipment used in these generation plants, illustrating that the energy harnessed comes from beneath the Earth's surface.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: bifermentans in animal feces or farm manure was documented [48], some of them pose a pathogenic risk [49], however due to their metabolic activity, they can play an essential role in anteater digestion. Clostridium species can utilize large amounts of nutrients that cannot be digested by the host and produce lots of short-chain fatty acids, which play a noticeable role in intestinal homeostasis [50]. Bifidobacteria are considered a beneficial microbial group and their occurrence is being researched across different animal species [51]. The presence of Bifidobacterium spp. in anteater feces was in unstable counts and they were not the dominant cultivable bacterial group, as well as Bifidobacteriaceae family was not present among mainly occurred families in the fecal microbiome of captive Southern Tamanduas. Bifidobacterial species occurrence varied across animals and locations. Contact with other animal species and the presence of insects as feed or insect-based products in the anteater’s diet could potentially be the source of detected bifidobacteria [22, 37, 52, 53]. Including suitable prebiotic substrates with a bifidogenic effect in the diet of anteaters can be an option to increase their quantitative representation to support beneficial effects [54], because captivity and associated dietary changes, including missing natural prebiotics substrates [55], may be a factor for the low presence of bifidobacteria in the anteaters in this study. Similarly, the cultivable lactobacilli occurrence was variable and low, compared to other lactic acid bacteria such as Weissella spp. and pediococci, mainly Pc. pentosaceus. Interestingly, lactobacilli [56] and Pediococcus spp. can have many beneficial roles covering aspects such as immunomodulation [57], growth enhancement in farm animals [58, 59], and resistance to infection [60]. Another frequently detected coccus in the feces of all anteaters was Strep. lutetiensis, its role in the intestinal microbiota is somewhat unclear. However, published works indicate a possible pathogenicity [61, 62]. A zoonotic potential is also carried by Lc. garvieae. [SEP] Justify:

Output: The text contrasts the claim by highlighting that the presence and variation of microbial species, such as Bifidobacterium spp. and lactobacilli, differ across animals and locations. It specifically mentions that 'Bifidobacterial species occurrence varied across animals and locations' and notes that 'the cultivable lactobacilli occurrence was variable and low,' indicating that microbiome compositions are not identical among individuals.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: O. et al. 2019Dopamine: Functions, Signaling, and Association with Neurological DiseasesNeurobiol 39:31–59 S2010Dopamine reveals neural circuit mechanisms of fly memory33:457–464 J. Krause W. C. Davis R. L2008Olfactory memory traces in DrosophilaRes 169:293–304 H. J. Tong C. Tsuda H2010100 years of Drosophila research and its impact on vertebrate neuroscience: a history lesson for the futureNeurosci 11:514–522 S. Seto E. S2014Dopamine dynamics and signaling in Drosophila: an overview of genes, drugs and behavioral paradigms63:107–119 M2003Mushroom body memoir: from maps to modelsNeurosci 4:266–275 R. L. 2004Olfactory learningNeuron :31–48 K. Furukubo-Tokunaga K2005Induction of cAMP response element-binding protein-dependent medium-term memory by appetitive gustatory reinforcement in Drosophila larvaeJ Neurosci 25:7905–7913 K. Furukubo-Tokunaga K2009Distinctive neuronal networks and biochemical pathways for appetitive and aversive memory in Drosophila larvaeJ Neurosci 29:852–862 A. et al. 2016of and Memory in 12 W. G. Harris W. A. Benzer S1974Conditioned behavior in Drosophila melanogaster71:708–712 B. L. Bonini N. Dawson D. R. Quinn W. G1983Reward learning in normal and mutant 80:1482–1486 G. Davis R. L2001Molecular biology and anatomy of Drosophila olfactory associative learningBioessays 23:571–581 W. G. Dudai Y1976Memory phases in DrosophilaNature 262:576–577 S. Armstrong J. D. Kitamoto T. Kaiser K. Quinn W. G2000The amnesiac gene product is expressed in two neurons in the Drosophila brain that are critical for memoryCell 103:805–813 Y. Jan Y. N. Byers D. Quinn W. G. [SEP] Justify:

Output: The text does not provide any information regarding olfactory receptors functioning through quantum effects. It primarily consists of citations and references to various studies related to Drosophila and dopamine, while the claim specifically addresses a mechanism associated with olfactory receptors, which is not discussed in the provided text.


Input: Task: corroborate the claim using the given text. Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: It was reported (Dickson & Fanelli, 2005) that the total size of the plant has little effect on the specific cost, as a series of standard modular units is linked together to obtain larger power capacities. It was also reported (Panea et al. , 2010) that the modular units have a satisfying economic efficiency, because modular construction reduces installation time and costs. Ultimately, the economic viability of the geothermal power plant depends on its ability to generate revenue in the long-term. Advertisement 3. CO2 – based EGS for combined power generation& CO2 sequestration 3. 1. Enhanced geothermal systems (EGS) – developments & utilization EGS, also known as engineered geothermal systems, are reservoirs that have been stimulated(e. g. hydraulic stimulation) and engineered to extracteconomical amounts of heat from unproductive geothermal resources that lack heat-carrier fluid circulation, permeability and/or porosity. EGS is a new type of geothermal power technologyand has the potential to become a significant sustainable and renewable power source for the future (Grasby et al. , 2011, Kalra et al. , 2012). The EGS concept is currently the subject of several international research investigations and once brought to successful production, will significantly expand the regions where geothermal powergeneration is feasible. In an EGS, a fluid (typically cold water or brine) is injected and fractures are induced to form subsurface heat exchange systems. The heated fluid is then produced from a parallel well where heat can be used at surface to generate electricity (Huenges, 2010; Majorowicz& Grasby, 2010). Additional production-injection wells are drilled to extract more heat from large volumes of rock mass to meet power generation requirement (Azim et al. , 2010). This technology does not require conventional natural convective hydrothermal resources located at depth, nor an initial high permeability of the reservoir, for power generation(once linked with ORC power technology). A schematic diagram showing a typical EGS concept is shown in Figure 3. EGS has the potential for accessing the Earth’s vast resources of heat located at depth to help meet future increasing energy demands. The EGS concept has driven increased interest in widelydevelopment of this geothermal energy potential by orders of magnitude (Huenges, 2010; Majorowicz& Grasby, 2010; Azim et al. , 2010). [SEP] Justify:

Output: The text corroborates the claim by discussing Enhanced Geothermal Systems (EGS), which are designed to extract heat from the Earth’s subsurface and generate electricity. The explanation details how EGS utilizes injected fluids to extract heat, and mentions that this technology enables the economic extraction of geothermal heat, thereby aligning with the idea of harnessing heat from beneath the Earth’s surface for power generation.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: Granadaene-producing colonies were commonly detected in anteater feces and their presence may be related to insects as feed in the diet of captive anteaters [37]. Coliforms belong to common commensals of the gut microbiota, but they include opportunistic pathogens as well [63]. TBX medium is a selective, chromogenic medium for the detection and enumeration of E. coli in food products and animal feed, however, it seems to be suitable for detection of coliforms in FS [64, 65]. In this study, the medium allowed us to quantify both E. coli and other taxa of coliform bacteria such as Enterobacter spp. , Citrobacter spp. , and Klebsiella spp. in the anteater microbiota. The mentioned groups were quantified in relatively constant numbers and species variability. The TBX medium was not selective for enterococci, therefore, their presence is considered in the presented numbers of other coliforms. Interestingly, a fecal metagenomics study of Malayan pangolins [66] found several species that likely play roles in the digestion of cellulose and may be able to degrade chitin; including Enterobacter cloacae, Lactococcus lactis, and Klebsiella pneumoniae, which we detected as well as common commensals. Also, Cheng et al. [13] demonstrated the complex and diverse interactions between hosts such as anteaters, echidnas, and pangolins (of the orders Pilosa, Monotremata, and Pholidota, respectively) and their symbiotic microbiota that have provided adaptive solutions for nutritional and detoxification challenges. As well as spatially complementary cooperation involved in the degradation of ants’ and termites’ chitin exoskeletons was revealed. Their study contributes new insights into the dietary evolution of mammals and the mechanisms involved in the coordination of physiological functions by animal hosts and their gut commensals. It can therefore be assumed that metabolic functions of bacterial commensals of anteaters are associated with the ability to use specific substrates found in the diet of these hosts. ConclusionUsing application sequencing, the most represented taxa in the fecal microbiome of captive from four locations in the were determined at the phylum and family levels. The microbiome analysis in which anteater locations were considered, showed that the captive conditions significantly influenced the microbiome profile of the analyzed animal FS. [SEP] Justify:

Output: The text contrasts the claim by presenting evidence of variability in the microbiome composition of different species, particularly in anteaters, pangolins, and echidnas. It discusses the complexities and diversity of their respective microbiota, highlighting that the composition can vary significantly based on their diets and habitats, as evidenced by the unique colonization of specific bacteria such as Enterobacter spp. and Klebsiella spp. in anteaters. This suggests a lack of uniformity in microbiome composition across different individuals.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: Benzer S1976dunce, a mutant of Drosophila deficient in learning73:1684–1688 R. L. Dauwalder B1991dunce locus: learning and memory genes in the fly7:224–229 J. R. Skoulakis E. M. Han K. A. Kalderon D. Davis R. L1998Tripartite mushroom body architecture revealed by antigenic markers5:38–5128Saumweber T. et al. 2018Functional architecture of reward learning in mushroom body extrinsic neurons of larval Drosophila9 R. F2001Drosophila as a focus in olfactory research: mapping of olfactory sensilla by fine structure, odor specificity, odorant receptor expression, and central connectivityTech 55:284–296 A. et al. 2005Glomerular maps without cellular redundancy at successive levels of the Drosophila larval olfactory circuit15:982–992 A. M. Wang J. W. Axel R2002Spatial representation of the glomerular map in the Drosophila protocerebrumCell 109:229–241 T. Lee A. Luo L1999Development of the Drosophila mushroom bodies: sequential generation of three distinct types of neurons from a neuroblastDevelopment 126:4065–4076 Z. Davis R. L2009Eight different types of dopaminergic neurons innervate the Drosophila mushroom body neuropil: anatomical and physiological heterogeneityCircuits 3 J. Pandey R. Wasser M. Udolph G2011Orthodenticle is necessary for survival of a cluster of clonally related dopaminergic neurons in the Drosophila larval and adult brain6 C. et al. 2006Light-induced activation of distinct modulatory neurons triggers appetitive or aversive learning in Drosophila larvae16:1741–1747 K. S. Demchyshyn L. L. McConkey F. Forte M. A. Niznik H. B1995A primordial dopamine D1-like adenylyl cyclase-linked receptor from Drosophila melanogaster displaying poor affinity for benzazepinesFEBS Lett 362:131–138 K. A. Millar N. S. Grotewiel M. S. Davis R. [SEP] Justify:

Output: The text provided consists primarily of citations and references to various studies related to Drosophila and olfactory research, but it does not address or provide any information regarding the claim about olfactory receptors functioning through quantum effects. Therefore, it is irrelevant to the claim.