Input: Task: corroborate the claim using the given text. Claim: Autonomous vehicles use sensors and algorithms to navigate and make decisions. [SEP] Text: Encara que actualment hi ha diverses empreses automobilístiques i centres de recerca treballant en els dos temes, i en especial en alguns casos eliminant de l'equació el comportament humà, encara hi ha mancances en les configuracions, perquè un vehicle autònom siga capaç de prendre decisions òptimes, davant totes les possibles condicions disponibles en un trànsit vial. Ara bé, i tenint en compte els dos temes abans esmentats sobre els desenvolupaments en ajudes a la conducció, els investigadors preveuen a grans trets, que per assolir majors nivells de conducció autònoma en la propera dècada, és necessari estudiar com fer més eficients les interaccions autònomes entre vehicles. Per això, les interseccions vials són un exemple clau, on és possible analitzar casos d'interaccions d'alta complexitat entre vehicles, ja que es tracta d'una part de la infraestructura vial, on els vehicles comparteixen carrils, vies, creus o canvis de carril a voluntat, i que podria generar col·lisions en punts de conflicte i retards en els desplaçaments si no existeix una cooperació adequada. [SEP] Justify:

Output: The text corroborates the claim by discussing the advancements in autonomous vehicle technology, particularly mentioning the need for efficient interactions between vehicles. This implies the use of sensors and algorithms for optimal decision-making in complex traffic situations, aligning with the claim that autonomous vehicles navigate using these technologies.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: [34] have reported a negative correlation for increased Lactobacillus abundance in the cecum and ileum with weight of birds. This result emphasizes the need to be considerate of the type of Lactobacillus species, rather than the genus, when formulating probiotics applications. species in the poultry respiratory tract include Lactobacillus salivarius, Lactobacillus crispatus/acidophilus/gallinarum, Lactobacillus johnsonii/gasseri, Lactobacillus aviarius, and Lactobacillus reuteri [34]. Depending on the metabolic property and oxygen requirement of the bacteria, they can be classified as transient or colonizing species. For example, Lactobacillus aviaries is known as a transient species in the trachea because it is an obligate anaerobe found in relatively lower abundance [34, 37]. Experimental studies have demonstrated that Lactobacillus species exhibit immunostimulatory and antiviral properties [38,39,40]. Additionally, Lactobacillus acidophilus, Bifidobacterium bifidum, and Streptococcus faecalis species have been found to induce natural antibodies against various foreign antigens in chickens [41]. Table 1 A comprehensive summary of studies that present the most prevalent genera observed in the respiratory tract of poultryFull size tableIn addition to the complexity of the poultry respiratory microbiota, inconsistency exists regarding the microbial diversity within various sites in the poultry respiratory tract. One theory is that microbial diversity decreases posteriorly along poultry respiratory sites, from the nasal cavity to the lungs, which has been referred to as the island ecological model in human studies [42, 43]. This proposition is grounded in an ecological framework, suggesting that the nasal cavities serve as a microbiota mainland (source), with the highest richness and evenness of microbial species, acting as a source of microbial population for other respiratory sites (sink) [44]. Several poultry studies [18, 24, 45] are in conformation with this proposition. Interestingly, Abundo et al. [44] reported an exception to this model as BAL samples recorded significantly higher microbial diversity compared to the trachea. This exception is herein referred to as the spatial-anatomical model. [SEP] Justify:

Output: The text contrasts the claim by discussing various Lactobacillus species and their abundance in the poultry respiratory tract, implying that diet can impact the composition of the microbiome. The mention of factors such as 'microbial diversity' within different sites and the 'island ecological model' also suggests that changes in diet can influence microbiome diversity, contradicting the claim that diet has no impact.


Input: Task: pass the claim using the given text. Claim: Horizontal gene transfer is a mechanism by which bacteria can acquire new traits. [SEP] Text: Most of the bacteria in this dataset are aerobic mesophiles, even when pathogens are not included (Table S1). Of the archaea, 34 were anaerobes and 34 were (hyper)thermophilic (Fig. 2: Table S1). Twenty-three archaea were moderately halophilic while six were extremely halophilic (Table S1). Only four archaea were mesophilic aerobes living at normal salt conditions (Fig. 2: Table S1). However, this reflects current knowledge of archaeal diversity, i. e. , few major taxonomic divisions of archaea include representatives from aerobic non-extreme environments with complete genome sequences. For example, there are only two main types of archaea commonly found in the oxic ocean: Thaumarcheota and II Euryarcheota (Karner, DeLong & Karl, 2001). and IV Euryarcheota are also occasionally found in the ocean but have not been sequenced (Zhang et al. , 2015). Thaumarcheota are the main type of archaea in oxic soils (Bates et al. , 2011) and in oxic freshwater (Reitschuler, Hofmann & Illmer, 2016). There are at present only 11 known genera in the phylum Thaumarcheota, four of which are represented in our dataset (one is thermophilic). There are presently two known types of II Euryarcheota (Zhang et al. , 2015), one of which is included in our dataset. Figure 1: Tree of all the bacteria used in this study. For names see Table S1. The inner ring is the growth temperature range of the bacteria. The middle ring is the oxygen utilization potential of the bacteria. The outer ring represents the frequency of archaea-bacteria pairs enriched in reciprocal best hits (RBHs), where green represents 0–3 pairs, orange 4–24 pairs, and red 25+ pairs. Download full-size image DOI: 10. 7717/peerj. 3865/fig-1 Figure 2: Tree of all the archaea used in this study. For archaeal names see Table S1. The inner ring is the growth temperature range of the archaea. The middle ring is the oxygen utilization potential of the archaea. [SEP] Justify:

Output: The text provided discusses the diversity of bacteria and archaea, their classification, and specific characteristics, but it does not mention horizontal gene transfer or how bacteria can acquire new traits. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Autonomous vehicles use sensors and algorithms to navigate and make decisions. [SEP] Text: D'aquesta manera, en aquesta tesi es proposa una sèrie d'algoritmes distribuïts per al control del trànsit en interseccions, basats en l'intercanvi de comunicacions entre vehicles autònoms (interaccions locals) properes a les interseccions i on es mostren comportaments emergents en el trànsit, resultant en creus de forma cooperativa, segura i eficient, des de baixes a altes densitats de trànsit vehicular en les interseccions. Aquesta investigació es desenvolupa utilitzant simuladors de trànsit vial, amb carrers estil Manhattan; primer implementant escenaris menys complexos amb carrers urbans d'un carril, i després incrementant la complexitat amb múltiples carrils. [-] [EN] Since a couple of decades, the technological driving aids have gone growing at a dizzying pace with the intention of making these systems more efficient and safe. These driving aids have been covering failures that. . . [+] [EN] Since a couple of decades, the technological driving aids have gone growing at a dizzying pace with the intention of making these systems more efficient and safe. These driving aids have been covering failures that the researchers name "erratic driving" or "unsafe driving behaviors" and are arbitrary decisions taken by a human driver which endanger all road users. These bad decisions in addition to the increasing number of driving commutes in a city nowadays (post pandemic), show the need to continue doing technological proposals focused on where there are more complex interactions between vehicles when density increases; for instance, an intersection in rush hour. The developments in driving aids have been orientated in two topics: the first driving automation (- ADAS and - AV) and the second road traffic management (centralized or distributed algorithms to traffic control). Although there are currently several automotive companies and research centers working in the two topics, and in special in some cases removing the equation the human behavior, there are still lacks in the configurations for an vehicle autonomous be able to make optimal decisions front to all possible conditions available in a road traffic. [SEP] Justify:

Output: The text corroborates the claim by discussing the development of distributed algorithms for traffic control and the intention of these technological aids to make systems more efficient and safe. It mentions that advancements in driving automation, particularly in relation to autonomous vehicles (AV), focus on optimizing decisions in complex traffic conditions, aligning with the claim that sensors and algorithms are used by autonomous vehicles to navigate.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: This model is based on the concept that the unique anatomical and physiological functions of each distinct respiratory site dictate the richness and evenness of its microbial residents. This would imply that constant mucociliary clearance occurring in the trachea contributes to its reduced microbial richness in comparison to LRT sites, where microbial deposition contributes to its higher microbial diversity [46]. Indeed, further studies are needed to clarify whether poultry respiratory sites exhibit a source-sink or unique microbial diversity trend. Influencing factors on poultry respiratory microbiota community composition and diversityThe composition and diversity of the respiratory microbiota in poultry are influenced by various factors. These include intrinsic host-related factors such as bird type, breed, age, and genetics, as well as several extrinsic factors. Extrinsic factors include production system, sampling sites and methods, sequencing platforms, and methodologies (choice of PCR primers, regions to be sequenced, number of PCR cycles, DNA extraction protocols), as well as nutrition, antibiotics use, disease, and environmental stressors such as heat and litter quality. The interplay of these factors contributes to the complexity of the poultry respiratory microbiota. A synthesis of available information on the most decisive determinants of the poultry respiratory microbiota (presented in Fig. 2) are described below:Fig. 2Factors shaping community structure and diversity of poultry respiratory microbiota. The interplay between intrinsic factors (highlighted in orange) and extrinsic factors (highlighted in grey) significantly influences the community structure and diversity of the poultry respiratory microbiota. The respiratory site itself, shaped by distinct physiological functions, determines the microbial residents, resulting in unique bacterial communities across various respiratory sites. Additionally, avian species type governs microbiota composition, notably between chickens and turkeys. Age is a critical factor, with microbial colonization increasing until an age-independent plateau is reached. However, this process is impacted by diverse stressors, environmental conditions, and management practices. Factors such as ammonia pollution, heat stress, antibiotic usage, and pathogen presence, especially viruses, can disrupt microbiota balance, potentially leading to dysbiosis. Understanding these intricate relationships is crucial for a comprehensive comprehension of avian respiratory microbiota dynamicsFull size imageIntrinsic factorsAs highlighted in our description of the spatial-anatomical model of microbial diversity in the respiratory tract, the distinct physiological and adaptive functions of each respiratory site determine its specific microbial residents. [SEP] Justify:

Output: The text contrasts the claim by discussing various factors that influence the microbiota composition, specifically highlighting that nutrition is one of the extrinsic factors that can affect microbiome diversity. It states that nutrition, along with other factors like antibiotics, disease, and environmental stressors, plays a significant role in shaping the microbiota. This indicates that dietary changes can indeed impact microbiome composition.


Input: Task: pass the claim using the given text. Claim: Horizontal gene transfer is a mechanism by which bacteria can acquire new traits. [SEP] Text: 6), though it is true that we only have 4 aerobic mesophilic archaea in our dataset. Pathogens, either anaerobic or aerobic, were never enriched in RBHs. To validate these findings statistically, a series of tests were conducted to investigate factors associated with the number of shared genes between bacteria and archaea (Table 1). Since many of the bacteria and archaea are both anaerobic and thermophilic, we used a two-way to take into account both oxygen and temperature simultaneously. Indeed, each factor independently had a significant correlation with the number of shared genes between archaea and bacteria (p = 0. 001; Table 1). Figure 6: Phenotypes of bacteria and archaea that are enriched in shared genes. The bacteria that formed pairs enriched in shared genes (RBHs) with three or more archaea and the phenotypes associated with those archaea. Labels on the x axis describe the bacteria while color coding describes the archaea. Download full-size image DOI: 10. 7717/peerj. 3865/fig-6 Table 1: Statistical analyses. Overall summary of results. The groups for GC content were: low GC = 30–45, medium = 46–55, high = 56–70. value Temperature (1 way) 0. 614 0. 001 Oxygen (1 way) 0. 213 0. 001 GC content (1 way) 0. 082 0. 001 Salt (1 way) Not significant pH 0. 249 0. 008 Metabolism (1 way) 0. 045 0. 004 Pathogen vs Autotroph 0. 224 0. 001 Pathogen vs Heterotroph 0. 023 0. 006 Heterotroph vs significant Oxygen (2 way w/temp) 0. 170 0. 001 Anaerobic vs Aerobic 0. 405 0. 001 Anaerobic vs facultative 0. 324 0. 001 Aerobic vs facultative Not significant Temperature (2 way w/O2) 0. 547 0. 001 Hyperthermo vs Meso 0. 654 0. 001 Thermo vs Meso 0. 517 0. 001 Hyperthermo vs significant Oxygen (2 way w/GC) 0. 227 0. 001 GC content (2 way w/O2) 0. 099 0. 001 Low vs High 0. 235 0. 001 Medium vs High 0. 088 0. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the statistical analyses related to shared genes between bacteria and archaea without mentioning horizontal gene transfer or how bacteria can acquire new traits.


Input: Task: corroborate the claim using the given text. Claim: Autonomous driving technology aims to reduce human error in transportation. [SEP] Text: AbstractThe degree of vehicle automation is continuously rising in all modes of transport both on public traffic infrastructure and in-house transport within company grounds, in order to improve the productivity, reliability, and flexibility of transport. You have full access to this open access 2. Other autonomous systems developing in parallel, such as drones, show that completely new business models are developing in the field of logistics. Expected changes in logistic processes and in human labor in the systems will be discussed using a generic supply chain approach. The 2. 1 Transport SystemsTypical indoor applications of AGT systems connect production and assembly processes, incoming and outgoing goods areas as well as picking areas and warehouses. AGT systems and work robots, such as those for picking, palletizing, etc. , are frequently combined in a single apparatus. In in-house logistics, the encounter between humans and AGT/AGV systems was therefore always envisioned since AGT/AGV systems generally perform other functions as well, for example supporting the picking process. Early personal safety concepts worked with tactile, mechanical bars or bumpers [2]. Today, laser scanners are more widely used which, depending on the driving speed, can cover up to 7 m [2] and are frequently combined with other sensor technologies. The stabilization level plays a relatively minor role in in-house transport as the company itself maintains the floor surface in a drivable state. In early systems, the guidance level in the indoor component of in-house transports was generally implemented with electrical conductors embedded in the floors. Today the following different types for position recognition and positioning can be distinguished [3]: On the one hand, this includes the physical guide, implemented either as an active inductive guide path, as a magnetic tape or optical guide path. On the other hand, technologies for free navigation which utilize floor markings (metal, magnets, transponders) or laser technology in which position-determination functions something like in maritime transport (cross bearing) can be found. Newer technologies combine laser scanners and camera systems with digital-environment maps and enable navigation by characteristics of the environment. Data transmission between the stationary and mobile units of an AGT system was previously conducted using inductive or infrared data transmission. Today, narrowband and increasingly broadband transmission (WLAN) are predominant. Radio direction finding enables localization via indoor GPS (System) with an accuracy up to 0. [SEP] Justify:

Output: The text corroborates the claim by discussing the increasing degree of vehicle automation across various modes of transport with the goal to improve productivity and reliability in transport systems. This aligns with the notion that autonomous driving technology is developed to minimize human error and enhance operational efficiency in the logistics and transportation sectors.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: Hence, it is not surprising that the respiratory site under consideration is a factor that potentially influences microbiota composition and diversity. Several poultry studies have reported distinct bacterial communities across different respiratory sites [5, 24, 25, 34]. Sohail et al. [12] also reported distinct spatial bacterial ecology between the ceca and trachea using Polymerase chain reaction/denaturing gradient gel electrophoresis (PCR/DGGE) fingerprinting methodology. Tracheal samples were predominantly dominated by and Oscillospira whereas cecal samples had Aerococcus, Anaerococcus, Globicatella, Lactobacillus, Nosocomiicoccus and Staphylococcus as the prevailing genera in their study. In conformation with results from Sohail et al. [12] study, Kallapura et al. [47] also reported a higher rate of Salmonella recovery in the trachea compared to the ceca. This disparity could possibly be because of the two mucosa milieus, the trachea is the easiest route for microbe entry and colonization. Additionally, longer feed retention time, and lower pH afford the ceca its unique bacterial composition and diversity [48]. Taylor et al. [18] provided unique perspective on the peculiarity of the poultry respiratory tract microbiota, as they report unique microbiota compositions of the avian trachea and nasal cavity. It is speculated that the avian trachea harbors more transient species compared to the nasal cavity. Similar observations have been reported in the human respiratory tract [6, 49]. Furthermore, the type of poultry bird is another factor that reportedly dictates the composition and diversity of the poultry respiratory tract microbiota. Although some bacterial taxa overlap occur, distinct differences in the URT microbiota (trachea) of chickens and turkeys have been reported [9]. Kursa et al. [9] further showed that the chicken trachea harbors significantly greater bacterial diversity compared to the turkey trachea. This difference in respiratory microbiota composition and diversity is speculated to be confounded by the age of the flocks, as the average age of chickens and turkeys from which samples were obtained in the study was 30 and 25 weeks, respectively [9]. The impact of age on the composition and diversity of the microbial communities in the avian respiratory tract has received less attention compared to the gut. [SEP] Justify:

Output: The text contrasts the claim by discussing how various factors, including the type of poultry bird and environmental conditions, influence microbiota composition and diversity. It highlights that the unique characteristics of different respiratory sites, such as the trachea and ceca, lead to distinct bacterial communities, indicating that external factors can significantly impact microbiome composition.


Input: Task: pass the claim using the given text. Claim: Horizontal gene transfer is a mechanism by which bacteria can acquire new traits. [SEP] Text: However, the three variables were significant in determining the number of shared genes for different COG categories. %GC was only significant for COG categories Synthesis, Energy Production, and Nucleotide Synthesis. Interestingly, oxygen utilization was significant for more COG categories than temperature, including Transcription, Energy Production, and Coenzymemetabolism. Additionally the category was significant for temperature, but not oxygen utilization. These results demonstrate that the genes shared among anaerobes are different than the genes shared among thermophiles. Table 2: Statistical analyses of shared genes split into COGs. COG summary between bacteria where the number of reciprocal best hits has been corrected for genome size. Oxygen and temperature were assessed in a two way. GC content was assessed taking oxygen into account in a two way. For the a Bonferroni correction was used by dividing the p value needed (0. 05) by 15 tests. Tests were only considered significant when p < 0. 003. Acid Synthesis, all three variables (oxygen, temperature and %GC) were significant. Temperature and oxygen utilization were still signification after both genome size and %GC were corrected for simultaneously. COG O2 Utilization anaerobe vs aerobe Temperature hyperthermo vs mesophile GC Low vs high = 0. 221 p = 0. 001 R = 0. 763 p = 0. 001 NS = 0. 271 p = 0. 001 = 0. 117 p = 0. 002 R = 0. 556 p = 0. 001 NS R = 0. 170 p = 0. 001 R = 0. 536 p = 0. 001 R = 0. 379 p = 0. 001 Carbohydrate NS R = 0. 655 p = 0. 001 NS Secondary metabolites R = 0. 451 p = 0. 001 R = 0. 166 p = 0. 001 NS = 0. 253 p = 0. 001 = 0. 571 p = 0. 001 NS R = 0. 247 p = 0. 001 Inorganic ion R = 0. 215 p = 0. 001 R = 0. 465 p = 0. 001 = 0. 612 p = 0. 001 Posttranslational modification R = 0. 402 p = 0. 001 NS NS Cell wall unknown R = 0. 352 p = 0. 001 R = 0. 609 p = 0. 001 NS General function R = 0. 380 p = 0. 001 R = 0. [SEP] Justify:

Output: The text does not address the claim regarding horizontal gene transfer. Instead, it discusses statistical analyses of shared genes among bacteria with respect to various environmental factors, such as oxygen and temperature, without mentioning horizontal gene transfer as a mechanism of trait acquisition.


Input: Task: corroborate the claim using the given text. Claim: Autonomous driving technology aims to reduce human error in transportation. [SEP] Text: 5 m, with outdoor GPS precise to within 10 m, dGPS (Differential GPS) accurate up to 1 m and dGPS with phase evaluation precise to within 0. 1 m. Vehicles are assigned to driving tasks and are coordinated [2]. The control concept consists of a control unit through which execution of the transport order, transport order processing, vehicle allocation and transport execution are managed centrally. The traffic control system is part of the vehicle job execution. Clearance for individual sections of the route is done similarly to the rail traffic system in block sections that can only be occupied by one vehicle at a time. One such system was implemented in the distribution center of a logistics service provider in 2011 [3]. In the picking process, AGT systems are used in which the pickers are carried by the vehicle as well. The safety of the picker is ensured through various measures, as with the safety regulations for rail transport in which passengers are required to assume a particular position with their hands and feet. It is therefore not possible to carry out other activities while the vehicle is in motion. The operator safety concept relies on laser scanners. Navigation relies on a magnetic point sequence guide system, and the control system utilizes wireless-technology for data transmission. The AGT/AGV control system is also handled centrally in the new systems. Expanding the systems is therefore always associated with major expenses, so research into autonomous, decentralized control solutions is afoot here as well. One current example is the autonomous reach forklift truck developed in the “marion (mobile, autonomous, cooperative robots in complex value creation chains)” project, which in turn was developed as part of the “Autonomik” (autonomous and simulation-based systems for SMEs) technology program. The tasks of vehicles are assigned by a superordinate system. The forklift executes the task autonomously and calculates and determines the optimal route independently. It is equipped with a 3D-laser, laser scanner and cameras for 3D environment detection. Through sensors, the forklift can precisely assess the environment, the object dimensions and its spatial position. One example of a decentralized control system has been developed in the project “decentralized, agent-based self-control of automated guided transport systems” [4]. In this system, various agents are modeled for each vehicle. Route planning and task assignment take place cooperatively. [SEP] Justify:

Output: The text corroborates the claim by describing various autonomous driving technologies and their functionalities. It emphasizes how vehicles can execute tasks autonomously, calculate optimal routes, and utilize sensors for precise assessment of their environment. These features indicate that such technology is designed to enhance safety and reduce human error in transportation, aligning with the claim.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: While there have been several poultry studies demonstrating unique age-driven shifts in microbial composition across different intestinal sites [50,51,52], the role of age in the poultry respiratory microbiota remains relatively understudied. The first study to provide insight into the role of age on the poultry respiratory microbiota was conducted by Shabbir et al. [5], which characterized the lower respiratory microbiome of birds from different age groups (36, 40 and 55 weeks) from three different farms in the Punjab province of Pakistan. While the study reported unique differences in microbiota composition and diversity across the evaluated samples, it is difficult to attribute the observed effects solely to the age of the flocks. Multiple confounding variables from experimental design, including differences in sex, bird type (layers vs breeders), production system (open-house vs. free-range vs. controlled-house), and small sample size could have contributed to the observed outcome. The comparative study of Glendinning et al. [24] offered better perspective on the effect of age on the respiratory microbiota. The study reported different nasal microbiota composition from birds of different age groups, and it was found that two-day old and three-week-old birds recorded a high abundance of Lactobacilli. However, 30-month-old birds recorded a lower abundance of Lactobacilli, while Jeotgalicoccus and Staphylococcus were the most abundant genera in the 30-month-old birds. Additionally, microbial richness and diversity increased in buccal and nasal samples with increasing age, except for BAL samples. Another study by Ngunjiri et al. [25] reported a significant shift in nasal microbial communities in layers at 16–25 weeks of age compared to brooding (0–5 weeks of age) and grow-out (6–16 weeks of age) stages. This finding is also supported by the results from Kursa et al. [9] study, which showed increased numbers of unique Variant (ASV) in tracheal samples as turkeys aged, suggesting increased microbial richness with increasing age. Interestingly, a similar observation was also noted for chickens in the same study. While these findings help to justify that a direct linear relationship exists between bird age and microbial composition and diversity in the respiratory tract, this may not be the case. Our speculation is that during the first weeks of life, microbial colonization and diversity increases until an age-independent microbial stabilization plateau is reached. [SEP] Justify:

Output: The text contrasts the claim by describing several studies that indicate age-related changes in microbiome composition and diversity, implying that factors such as age can significantly affect microbiome characteristics. This suggests that environmental changes, including diet, could also impact microbiome composition, thus rebutting the assertion that diet has no influence.


Input: Task: pass the claim using the given text. Claim: Horizontal gene transfer is a mechanism by which bacteria can acquire new traits. [SEP] Text: Fuchsman, Collins, and were all supported as IGERT trainees in Astrobiology under NSF grant 05-04219. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. 2011. Horizontal gene exchange in environmental microbiota. Frontiers in Microbiology 2 2006. The marine viromes of four oceanic regions. PLOS Biology 4(11):e368 ämpfer P, Staley JT. 2006. Psychromonas ingrahamii sp. nov. a novel gas vacuolate, psychrophilic bacterium isolated from Arctic polar sea ice. of Systematic and 56:1001-1007. 2010. A thermophilic bacterial origin and subsequent constraints by redox, light and salinity on the evolution of the microbial mercuric reductase. 12:2904-2917 Bates ST, Berg-. 2011. Examining the global distribution of dominant archaeal populations in soil. 5:908-917. 1991. Understanding bacterial biofilms. Trends in Biotechnology 9:138-143 Boto L. 2009. Horizontal gene transfer in evolution: facts and challenges. Proceedings of the B: 277:819-827 Brochier-Armanet C, Deschamps P, López-García P, Zivanovic Y, Rodríguez-Valera F, Moreira D. 2011. Complete-fosmid and fosmid-end sequences reveal frequent horizontal gene transfers in marine uncultured planktonic archaea. 5:1291-1302 Chang Y--öker -P, Lapidus A. 2011. Non-contiguous finished genome sequence and contextual data of the filamentous soil bacterium Ktedonobacter racemifer type strain (SOSP1-21) Standards in 5:97-111 Christensen H, Hansen M, Sørensen J. 1999. Counting and size classification of active soil bacteria by fluorescence in situ hybridization with an rRNA oligonucleotide probe. Applied and 65:1753-1761 Clarke KR. 1993. Non-parametric multivariate analyses of changes in community structure. of Ecology 18:117-143 Cordero OX, Hogeweg P. 2009. The impact of long-distance horizontal gene transfer on prokaryotic genome size. [SEP] Justify:

Output: The text is largely irrelevant to the claim as it mainly lists various studies and authors related to microbiology without directly addressing or supporting the idea of horizontal gene transfer as a mechanism for trait acquisition in bacteria. Although it mentions 'horizontal gene transfer' in a general context, it does not provide information or evidence that corroborates the claim.


Input: Task: corroborate the claim using the given text. Claim: Autonomous driving technology aims to reduce human error in transportation. [SEP] Text: Simulations showed a reduction in the overall route distances of all AGVs, a roughly 8 % drop in the empty trip share, a 22 % decrease of lead times and a minor increase of the utilization rate of the AGVs [5]. At the Fraunhofer-Institute for and Logistics (IML), a cellular transport system based on swarm intelligence was developed in the “for Logistics” project. In this system, the swarm (the means of transport) receives the transport jobs, the nearest vehicle takes on the job and dynamically determines the shortest path. 2. 2 on Private PropertyOutdoor applications for autonomous vehicles on private property are AGT systems for heavy transports or in-plant shuttle traffic are common, as the following examples demonstrate. At a container terminal, automated guided vehicles move containers between the container cranes and the stacking area [6]. The objective is to shorten routes, reduce empty trips and achieve optimal utilization of all resources. Transponders installed in the ground are used for positioning. Route planning is done independently, as are battery changes. Coordinating control is conducted via radio data transmission. In Germany, a major cooperation behind driverless trucks is a company that was originally active in the radio technology sector. In 2012, for example, this company implemented a driverless truck-shuttle between the production and logistics buildings on the factory grounds of a dairy company [7]. Loading and unloading of the pallets laden with fresh products and packaging materials are done automatically. The lane-guidance system utilizes transponders in the pathway. A sensor is installed beneath the towing vehicle that uses the markings on the floor for orientation and route determination. Aided by steering rear axles, the vehicles can drive small envelopes and achieve positioning precision to within 2 cm. Laser scanners scan the environment and together with contact switch strips and emergency stop buttons ensure the safety of people, goods and the vehicle itself. The “Sichere autonome Logistik- und Transportfahrzeuge (SaLsA)” [“Safe autonomous logistics and transport vehicles”] project led to further developments that made the encounter between AGT systems, trucks and people in the outdoor environment safer [8]. In the outdoor environment, the safety concept consists of radar sensors, since laser scanners are not permitted there. [SEP] Justify:

Output: The text corroborates the claim by discussing various autonomous guided vehicle (AGV) systems that utilize advanced technologies to perform tasks such as route planning, positioning, and cargo handling with minimal human intervention. These systems are designed to reduce empty trips, optimize resource utilization, and ensure safety through automated controls and sensors, ultimately aiming to minimize human error in transportation operations.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: Several factors, including the environment, stressors, and nutrition could potentially contribute to when the microbial plateau is achieved. A good buttress of this hypothesis is the observed significant taxonomic successional difference in the microbiota of old and young layer chickens [25]. As old layers are more exposed to several physiological and management stressors, they undergo more microbial plasticity compared to younger hens, implying they take a longer time (age) to reach a microbial stabilization plateau. Furthermore, the study by Taylor et al. [18] suggested that there might be a respiratory-site specific effect of age on poultry respiratory microbiota. The study reported significant differences in species richness and evenness in the nasal cavity compared to the trachea. Anatomically, the nasal cavity's constant interaction with the external environment may explain the observed difference. Summarily, while age plays a significant role in shaping the poultry respiratory microbiota, other factors may also contribute to the observed microbial composition and diversity. Further studies are thus needed to provide more insight on the complete role of age on poultry respiratory microbiota. Extrinsic factorsIt is common knowledge that a bird’s phenotype is largely influenced by its genotype and environmental influence. Hence it is not surprising that the environmental conditions of a bird affect its respiratory microbiota composition and diversity. For instance, the immediate environment of a poultry bird includes litter, feces, and moisture. All of which can potentially serve as a viable ground for pathogenic bacteria proliferation, depending on the stocking density, management conditions, and other factors. et al. [53] revealed that litter management could influence the respiratory microbiota of broiler chickens via an increase in atmospheric bacteria load. The authors conducted a longitudinal study to evaluate the effect of ambient air in a tunnel-ventilated broiler house on the tracheal microbiota. The tracheal microbiota was dominated by Escherichia coli/Shigella at week 3 of their study, which was correlated with litter aeration by tumbling. While litter aeration increases aerosols in the bird-rearing facility, it also prevents litter compaction brought on by moisture buildup from bird excrement, drinker leakage, and other factors [54]. Ivulic et al. [53] found that air tumbling as a management strategy reduced microbial diversity in the same period across the broiler rearing facilities in their study. [SEP] Justify:

Output: The text contrasts the claim by describing how various factors, including nutrition, can influence the composition and diversity of microbiota. It explains that environmental conditions and management practices, which are linked to dietary changes, significantly affect the microbial composition in poultry. The consideration of nutrition as a factor contributing to microbial diversity suggests that diet can indeed impact microbiome composition, directly opposing the claim that diet has no effect.


Input: Task: pass the claim using the given text. Claim: Fossil records provide critical evidence for understanding evolutionary processes. [SEP] Text: ResultsPlastome featuresThe sampled WCS plastomes showed a typical quadripartite structure, encompassing a large single-copy (LSC) region and a small single-copy (SSC) region separated by two inverted repeat (IRa and IRb) regions (Fig. S1; Tables S1, S2 and S3). The genome sizes ranged from 158,149 bp to 160,861 bp, and GC content varied from 37. 7 to 38. 2% (Table S3). The WCS plastomes were highly conserved in terms of gene content and structure (Fig. S2; Tables S3 and S4), and they possessed 115 unique genes, including 81 protein-coding genes (PCGs), 30 transfer RNAs (tRNAs), and four ribosomal RNAs (rRNAs). Except for the pseudogenization of ycf15 in Chunia bucklandioides, none gene deletion was found in the WCS plastomes (Fig. S2). Phylogenetic relationshipML and BI analyses yielded highly congruent tree topologies (Figs. S3 and S4), which resolved Altingiaceae, Cercidiphyllaceae, Daphniphyllaceae, and Hamamelidaceae as fully supported [posterior probability (PP) = 1. 0, bootstrap support (MLBS) = 100%] monophyletic lineages (Fig. 1). Within the WCS, the successive sister relationship of Altingiaceae (PP = 1. 0, MLBS = 100%), the clade including Cercidiphyllaceae and Daphniphyllaceae (PP = 1. 0, MLBS = 80%), and Hamamelidaceae (PP = 1. 0, MLBS = 84%), were recovered. The MP reconstruction also fully supported the monophyly of Altingiaceae, Cercidiphyllaceae, Daphniphyllaceae, and Hamamelidaceae. However, the interfamilial relationships (the successive sister relationships of Daphniphyllaceae, Altingiaceae, Cercidiphyllaceae, and Hamamelidaceae) that recovered by the MP phylogeny is different from those resolved by the BI and ML phylogenies (Fig. 2). Fig. [SEP] Justify:

Output: The text does not address the claim about fossil records and evolutionary processes. Instead, it focuses on the structure and features of plastomes, along with phylogenetic analyses, which are not directly related to fossil records or evolutionary evidence.


Input: Task: corroborate the claim using the given text. Claim: Autonomous driving technology aims to reduce human error in transportation. [SEP] Text: The cooperative scanning of the environment through mobile and stationary sensors enables safe operation even at higher speeds (economic viability). 2. 3 for of Plant GroundsThe development of autonomous vehicles for freight transport and logistics outside of plant grounds is primarily conducted on a problem-oriented basis. So called driving robots were developed for use in dangerous situations, e. g. for disarming munitions, or for use in difficult-to-access areas such as deep-sea exploration, work on mountain sides or in dense forests and remote areas such as for work in the mining sector. Very large automated trucks with a maximum load capacity of 290 metric tons have been used at one of the world’s largest iron-ore mines in Australia since the 1990s [9]. The reason for their development was primarily difficulties in staffing, the dangerous shift work in the outback and the demanding logistical requirements in terms of personnel planning and staff transfer. Navigation is done via radar and lasers as well as through the use of waypoints for orientation. Monitoring and intervention options are possible via an operation center using wireless transmission. Control is carried out via GPS and dead reckoning, such as in ships or aircraft, through continuous position determination by means of measuring the course, speed and time. 2. 4 Development of in of TransportOther means of transport, in which technical systems for stabilization, navigation (e. g. digital maps) and environment cognition are used have also seen increasing degrees of automation. Aircrafts have been equipped with stabilization systems since the early 20th century, autopilot functions are a long-established feature and the first drones in Germany are already in use in military, police and firefighting applications. Unmanned aerial systems or unmanned aerial vehicles (UAVs) are also used in civil applications in other countries, replacing for example ranchers and inspectors in remote areas. Drones monitor and seed fields and perform pest control functions. Small drones are already in use in Germany as well, for example for inspecting damage caused by storms or fires, in film productions and industrial inspections. (the by far largest German railway company) is currently testing drones for monitoring vehicles and infrastructure. There are also pilot studies under way in the area of transporting commercial goods, in particular packages. With a carrying capacity of up to 2. 5 kg and a range of approximately 15 km, current drones could for example be used to deliver food or medications. A drone that can be used to transport a defibrillator has also been tested. [SEP] Justify:

Output: The text corroborates the claim as it discusses various applications of autonomous technology, including the use of ‘driving robots’ developed for dangerous situations and environments. It highlights how the development of vehicles, such as large automated trucks used in mines, has been driven by the need to overcome staffing difficulties and enhance safety in hazardous conditions. This aligns with the claim, emphasizing that autonomous driving technology is indeed designed to improve safety and reduce human error in transportation.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: High atmospheric bacterial load and temporal increase in ammonia levels in the barn facilitated by the litter aeration by tumbling are deemed responsible for the unique tracheal microbiota composition observed in their study. Poor barn ventilation, which results in high ammonia and dust concentrations, can be predisposing factors for pathogenic E. coli, such as Escherichia coli (APEC) colonization of the bird respiratory tract [55]. In light of the implications of APEC, on bird health and welfare, it is imperative to closely examine innovative strategies for managing litter and barn environmental air. Furthermore, Ivulic et al. [53] reported a succession of tracheal microbiota from Escherichia coli/Shigella to Gallibacterium sp. at week 6, this reinforces the transient nature of E. coli observed at week 3. Additionally, given that microbiota dysbiosis often leads to inflammatory reactions [56, 57], it is plausible that the immuno-mucociliary clearance in the trachea contributed to the observed microbial succession. As highlighted above, ammonia pollution in poultry barns may promote pathogenic microbial colonization in the respiratory tract, which in turn disrupts respiratory health [58, 59]. The avian trachea is thought to be affected by ammonia stimulation, resulting in a concurrent shift in the microbial composition. Zhou et al. [13] confirmed this in their study which evaluated the effects of varying levels (0–35 ppm) of ammonia on broiler chicken tracheal microbiota. Exposure to 15–35 ppm levels of ammonia disrupted microbial homeostasis in the trachea, as evidenced by reduced alpha and beta diversity. Increasing levels of ammonia exposure also increased the communities of Blautia and Streptococcus. Species from both genera have been linked to multiple respiratory pathologies and are capable of preventing the colonization of symbiotic bacteria [60, 61]. This result emphasizes the necessity of implementing innovative litter management and anti-pollution strategies. Environmental stress, such as heat stress, is another factor that can induce a shift in respiratory microbiota. Oxidative stress, immunosuppression, inflammatory conditions, and microbial dysbiosis are a few of the negative impacts that heat stress can have on poultry [62, 63]. Relative to the intestine, the impact of heat stress (HS) on the respiratory microbiota is understudied. [SEP] Justify:

Output: The text contrasts the claim by discussing the significant impact of environmental factors, such as ammonia levels and heat stress, on the microbiome composition, particularly in avian respiratory systems. The observation that exposure to varying levels of ammonia disrupted microbial homeostasis and resulted in shifts in microbial communities indicates that external factors, including diet and management practices, can indeed affect microbial composition.


Input: Task: pass the claim using the given text. Claim: Fossil records provide critical evidence for understanding evolutionary processes. [SEP] Text: Previous studies have revealed that both BI and ML phylogenies are more resistant to long-branch attraction than MP phylogenies [73,74,75]. The following discussion is mainly based on the BI and ML tree topologies because the interfamilial relationships recovered from the BI and ML phylogenies can be more reliable than those recovered from the MP phylogenies. In this study, both BI and ML phylogenies recovered three successively divergent clades within the WCS, corresponding to Altingiaceae, Cercidiphyllaceae + Daphniphyllaceae, and Hamamelidaceae. The interfamilial relationships are consistent with those revealed by Jian et al. [21], Soltis et al. [27], Xiang et al. [30], Tarullo et al. [31], and Bi et al. [33]. Nevertheless, the interfamilial relationships recovered in this study are inconsistent with those obtained by analyzing plastid sequence data alone, which proposed topologies of (Daphniphyllaceae, (Altingiaceae, (Hamamelidaceae, Cercidiphyllaceae))) [32, 77], (Altingiaceae, (Cercidiphyllaceae, (Daphniphyllaceae, Hamamelidaceae))) based on 83 plastid PCGs of four species [52], (Hamamelidaceae, (Cercidiphyllaceae, Daphniphyllaceae, Altingiaceae)) based on 83 protein-coding genes, and ((Daphniphyllaceae, Altingiaceae), (Hamamelidaceae, Cercidiphyllaceae)) based on plastome of nine species [53]. Due to the limited taxonomic sampling of the WCS, these studies likely suffered from phylogenetic errors. Based on a more comprehensive sampling of the WCS taxa at the genus level and the concatenated 78 plastid PCGs that contains more sequence variations and phylogenetically informative sites than was available in previous plastid phylogenetic studies, the deep relationships within WCS recovered in this study were robustly supported. This led to the recovery of the maternal backbone phylogeny of the WCS, providing new insights for inferring the evolutionarily complex events that likely caused the phylogenetic recalcitrance of the deep relationships within WCS. [SEP] Justify:

Output: The text does not address the claim regarding fossil records and their role in understanding evolutionary processes. It focuses on phylogenetic relationships, methods, and the implications of various phylogenetic analyses without directly linking to fossil evidence or its significance in evolutionary studies.


Input: Task: corroborate the claim using the given text. Claim: Autonomous driving technology aims to reduce human error in transportation. [SEP] Text: They do differ in terms of the degree of autonomy, though. 3 in the Field of TransportBuilding on the experiences described here, the following will sketch potential applications for autonomous vehicles in the field of freight transport using the generic use cases described in Chap. 2. The focus is on the transport of a specific good in road freight traffic. Potential applications in further segments of commercial transportation such as passenger transportation and goods transport in the context of production (self-driving work machines) are not examined here. Based on a conceptual description of the respective use case and in light of the specific features, an initial estimation of the benefits, opportunities and risks of introducing such a technology will be discussed. The examination will begin, however, with a consideration of the degrees of automation in driving for freight transport, in order to better distinguish the implications of the various use cases. 3. 1 Excursus: Degrees of Automation in TransportTo assess the necessity and benefits of a certain degree of automation in freight transport, first we will return to the definition of the driving task according to [13], whereby it is described as follows: The safe execution of the driving task requires information and knowledge regarding the traffic situation on the guidance level, the driving surface on the stabilization level, as well as the road network on the navigation level. Safe conduct of the vehicle requires steering, acceleration and braking as well as decisions regarding speed and course for longitudinal and lateral control of the vehicle. The decisions required for this are made on the basis of information regarding environmental conditions and the associated knowledge of the action to be taken. categorizes automated driving into four development levels [14]: assisted driving (1), partially automated driving (2), highly automated driving (3) and fully automated driving (4). In the first three levels, the system performs partial aspects of the driving task for a specific time and/or in specific situations. But the driver is available at least as a supervisory organ. For the last level of fully automated driving (4), [14] presumes that the vehicle is navigating freely and no driver is required as a fallback level. In the area of freight transport, automated guided transport systems exist even on low automation levels. With an intermediate level between (3) and (4), another relevant variant in transport practice can be observed: The vehicle is highly automated and driverless, but free navigation does not occur. In many cases, the vehicle is controlled remotely by an operator via a control center. 3. [SEP] Justify:

Output: The text corroborates the claim by discussing the various levels of automation in driving, particularly emphasizing the role of these technologies in enhancing safety and efficiency. By outlining how different levels of autonomous driving range from partial automation to fully automated systems, the text implicitly supports the claim that the ultimate goal of such technologies is to minimize human error and improve the safe execution of driving tasks.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: Several poultry studies [64,65,66,67] have recorded unique shift in gut microbiota in response to heat stress. In terms of the respiratory tract, Wang et al. [10] reported reduced bacterial richness and diversity in the lung microbiota of cyclic heat-stressed (30 °C, 10 weeks) layer-type pullets compared to their thermoneutral counterpart (24 °C). In terms of microbiota composition, significant reduction in members of the genus Brevibacillus was also recorded in the heat-stressed birds. This is a notable observation given that Brevibacillus species are often considered for probiotic use due to their ability to secrete antimicrobial peptides that can hinder the growth of pathogenic microorganisms [68]. In conformity with Wang et al. [10] result, Sohail et al. [12] also recorded reduced tracheal microbial diversity in broiler chickens subjected to chronic HS (35 ± 2 °C, 42 days). Additionally, their study provided insights into the limitations of popular methods utilized in microbiome research, particularly related to taxonomic resolution, such as PCR-DGGE and 16S rRNA throughput sequencing. Results obtained using PCR-DGGE showed that the impact of HS on the ceca was more pronounced compared to trachea. Moreover, dietary supplementation with mannooligosaccharides was found to restore tracheal microbial homeostasis in heat-stressed birds. In addition to identifying differences in microbial composition between HS and thermoneutral groups, the use of 16S rRNA high throughput sequencing provided distinct bacterial clades and relative abundances between treatment groups at a much lower taxonomic resolution. Taken together, these results demonstrate that HS induces respiratory microbiota community disruption and microbial diversity reduction. The extent of this microbial dysbiosis resulting from HS may vary based on factors such as the type, intensity, and duration of the stress [69]. Therefore, it is crucial to continue studying heat stress intervention strategies for the poultry industry, as the documented effect of reduced microbial diversity on decreased resistance to opportunistic infections has been well-established [70, 71]. Although yet to be fully explored, antibiotic use is another factor that can influence the poultry respiratory tract microbiota community structure. For over six decades, antibiotics have been used at sub-therapeutic doses to enhance the growth performance of poultry flocks [72]. [SEP] Justify:

Output: The text contrasts the claim by illustrating that dietary supplementation with mannooligosaccharides can restore tracheal microbial homeostasis in heat-stressed birds. This suggests that changes in diet can indeed impact microbiome composition and diversity, countering the assertion that diet has no effect.


Input: Task: pass the claim using the given text. Claim: Fossil records provide critical evidence for understanding evolutionary processes. [SEP] Text: Topologically, the deep relationships of the WCS recovered in this study are incongruent with those recovered based on the phylogenomic analysis of target-capture sequencing and transcriptome data [28], which proposed a successive divergence of Daphniphyllaceae, Cercidiphyllaceae, Altingiaceae, and Hamamelidaceae with robust support for each node. Based on these results, phylogenetic incongruence between plastid and nuclear data (cytonuclear discordance) was detected in the deep clades of the WCS (Fig. 4). Cytonuclear discordance is commonly observed in some phylogenetically recalcitrant plant lineages [16, 50, 78,79,80,81]; in most cases, nuclear phylogeny is more congruent with morphologic characteristics than plastid phylogeny, and such discordance is thought to be caused by hybridization [17, 50, 82, 83]. Fig. 4Comparison of deep relationships within the “woody clade” in Saxifragales. (A) Phylogenetic analyses of plastomes. (B) Phylogenetic analyses of target-capture sequencing and transcriptome dataFull size imageBy comparing the plastome (this study) and nuclear genome phylogenies [28] with the morphological characteristics, we found that the interfamilial relationships recovered based on the analyses of target-capture sequencing and transcriptome data [28] are more consistent with the morphologies. Specifically, Altingiaceae has traditionally been treated as a member of Hamamelidaceae [10, 11, 13]. Both families are monoecious and have one or two-chambered anthers, distinct from the dioecism and four-chambered anthers of Cercidiphyllaceae and Daphniphyllaceae [23, 24, 26, 84]. These morphological affinities justify the close relationship between Altingiaceae and Hamamelidaceae. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses phylogenetic relationships and molecular data without mentioning fossil records or their role in understanding evolutionary processes. The focus is on the incongruence of phylogenomic analyses and morphological characteristics among certain plant lineages, which does not directly relate to the significance of fossil evidence.


Input: Task: corroborate the claim using the given text. Claim: Autonomous driving technology aims to reduce human error in transportation. [SEP] Text: 2 for TransportAssisted and partially automated systems are already common in series-production vehicles. They take over longitudinal and/or lateral control of the vehicle for a certain period of time and/or in specific situations. In the assisted systems, the driver is warned; in partially automated systems, the system assumes control. The impetus—for example braking—must still be provided by the driver. The most well-known driver assistance systems (DAS) are anti-lock brake systems (ABS) and electronic stability programs (ESP). Due to severe road accident, lane-change assistants, lane-departure warning systems and adaptive cruise control functions became mandatory for new vehicles ahead of schedule in 2013. Other systems are in development or are already ready for production, such as anti-rollover systems, cornering systems or parking systems. They are primarily focused on assisting the driver on the guidance and stabilization levels. Highly and fully automated vehicles can also navigate freely; they are situation- and infrastructure-independent. Fully automated systems can function without a driver. Not only activities on the navigation level are assumed by the driving robot, but also the activities that are necessary to return the system to a minimal-risk state when components fail. From the perspective of freight traffic and logistics, technological solutions for the stabilization and guidance levels are therefore not the primary focus. Of greater interest are the potential use cases with and without drivers and free navigation. A closer examination is conducted on the following distinctions in the use cases: 1. as highly automated highway driving with a driver and free navigation; 2. Demand as highly automated highway driving without a driver and with free navigation; 3. for Extended Availability—Follow-me Vehicle as highly automated driving without a driver and without free navigation (missing use case 3/4), 4. as highly automated driving without a driver and without free navigation (missing use case 3/4). In the following, the use cases will be introduced and initial arguments for and against the respective degree of autonomy in logistics and freight transport are presented. In each case it will be assessed to what extent the use cases in the freight traffic system coincide with the “of Autonomous Driving” (see Chap. 2) for private transportation, what differences exist and what the implications of such differences are for implementation. 3. 3 with Driver and Free NavigationInterstate pilot describes the use case in which an autopilot function is used, but a driver is available at all times. [SEP] Justify:

Output: The text corroborates the claim by discussing how various automated and partially automated systems are implemented to assist the driver and enhance vehicle control. It highlights that these systems aim to improve safety on the roads, thus implicitly reducing human error by taking over control in specific situations. For instance, driver assistance systems like anti-lock brake systems (ABS) and electronic stability programs (ESP) aim to help the driver in maintaining vehicle stability and avoiding accidents, directly supporting the goal of reducing human error in transportation.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: However, their continued use has been linked to public health concerns related to antibiotic resistance and residues, leading to calls for their reduction and ultimate discontinuation by governments and the general public [73]. Several studies [71, 74, 75] have affirmed that antibiotics are capable of inducing changes in microbial structure in the poultry gut. This antibiotics-induced shift in microbial structure has also been associated with decreased adaptive immune responses in poultry, particularly in a dose-dependent manner [76,77,78]. Conversely, only one study [18] investigated the influence of antibiotics on the poultry respiratory microbiota. In this study, commercial turkey flocks treated with chlortetracycline recorded a lower abundance of Mycoplasma in the trachea. The abundance of Mycoplasma was negatively correlated with the average weight of birds in the same study, which is notable considering a link between gut microbiota composition and bird weight has previously been established [79]. Vancomycin-colistin induced gut microbiota dysbiosis with concomitant impairment of lung immunity has also been reported in mice [80]. Despite these findings, further studies are required to fully understand the role of antibiotics in dysbiosis of the poultry respiratory tract and its effects on immunity and growth performance. Pathogens, especially viruses, have also been shown to cause respiratory microbiota disruption in humans [81,82,83]. This has recently been demonstrated in the poultry respiratory tract in a longitudinal study in which birds were challenged with low pathogenic avian influenza (LPAI) H5N2 virus [84]. Viral infection increased the total bacterial content in nasal microbiota samples; however, this increase had an inverse relationship with bacterial species richness. Samples retrieved from the nasal cavity also showed significant virus-induced change in beta diversity. Results from this study also suggest that virus-induced microbiota disruption is respiratory-site specific. Compared to the control treatment in this study, virus-induced microbial disruption across several taxa reduced linearly from the URT to the LRT. The number of microbial taxa disrupted by the LPAI H5N2 virus were 16, 5, and 1 across the nasal cavity, trachea, and lungs, respectively. [SEP] Justify:

Output: The text contrasts the claim by providing evidence of how antibiotics have been shown to induce changes in microbial structure in the poultry gut and respiratory microbiota. It discusses the implications of antibiotic use on microbial composition and health, indicating that antibiotic-induced shifts can occur. The mention of dietary influences is implied in the context of growth performance and gut microbiota composition, effectively countering the claim that diet has no impact on microbiome composition.


Input: Task: pass the claim using the given text. Claim: Fossil records provide critical evidence for understanding evolutionary processes. [SEP] Text: Among these, the plastomes of 27 species representing 10 genera were newly sequenced in this study (Table S1), and publicly available plastomes of 29 species representing 13 genera across four WCS families were obtained from the database (Table S2). The genomic DNA of these newly sequenced samples was extracted from approximately 100 mg of silica gel-dried leaf tissue using a modified CTAB method [87]. Then, the shotgun DNA libraries were constructed using a (Illumina, Inc. , ) following the manufacturer’s instructions. Paired-end sequencing was performed on an Illumina NovaSeq 6000 platform to generate approximately 4 Gbp of raw reads for each sample. Plastome assembly and annotationTrimmomatic v0. 40 [88] was used to filter low-quality Illumina raw reads with pre-set parameters. The pipeline GetOrganelle v1. 7. 7. 0 [89] was employed to assemble plastomes using Illumina clean reads with default parameters, using the plastomes of the corresponding species as a reference (Table S2). The assembled plastomes were further adjusted using Bandage v8. 0 [90] and annotated using the online program GeSeq [91]. Information on the initiation codon, stop codon, and intron sites of the protein-coding genes was examined and manually adjusted using Geneious v10. 2 [92]. tRNA genes were annotated using trnascan-SE v2. 0 [93]. The inverted repeat (IRa and IRb) regions of the plastome were determined using Geneious v10. 2 [92]. All WCS plastomes were progressively aligned with the complete plastome of Hamamelis mollis, as a reference, using the multiple genome alignment tool Mauve v4. 0 [94], after one of the inverted repeat regions was removed. Phylogenetic analysisGiven the close relationship between the WCS and Paeoniaceae [e. g. , 27, 52], eight Paeonia species were selected as outgroups. In total, 78 plastid PCGs (Table S4) commonly shared by the sampled plastomes were extracted from each plastome for phylogenetic analysis using PhyloSuite v1. 2. 2 [95]. The PCGs were aligned with MAFFT v7. [SEP] Justify:

Output: The text does not address the claim regarding fossil records and evolutionary processes. It focuses on the sequencing and analysis of plastomes from various species without discussing any aspect of fossil records or their importance in evolutionary studies.


Input: Task: corroborate the claim using the given text. Claim: Autonomous driving technology aims to reduce human error in transportation. [SEP] Text: The driver hands over the stabilization and guidance level (and thus also navigation) to the autopilot, ideally after specifying a destination address. The use of an interstate pilot is intended between entering and exiting the interstate. The driver assumes control when confronted with unclear driving situations (e. g. construction zones). The posited benefits of the interstate pilot are provided by the reduction of accidents and an improved traffic flow. Particularly in traffic jams or stop-and-go traffic situations, but also on long, monotonous journeys, as well as due to the ever-increasing time-pressure of modern life, drivers are often close to their performance limits. In addition to unburden the driver from stressful driving situations, the interstate pilot also creates free time that can be used for other purposes. Here there are deliberations as to whether activities such as route planning and fleet management might not also be decentralized. A first case of application has been already reported from as early as 1987, when the University of the in Munich, Germany, was experimenting with a lorry driving on a motorway [15]. In 2013, the vehicle-manufacturer Scania presented a truck that could “independently accelerate, brake and steer” up to a speed of 50 km/h [16]. In 2014, Daimler had a truck driving up to 85 km/h amid other vehicles on a closed section of interstate [17]. The envisioned interstate pilot is essentially enabling fully automated driving. Due to safety considerations, however, the concept still depends on an available driver, which in effect reduces the scenario to being only highly automated. The effective top speed and the higher maximum permissible mass together require different safety concepts than in private transportation. Changes are expected primarily in terms of the job description of the driver. To date, drivers have been obliged to learn much about vehicle technology and securing loads. Would the driver continue to perform the technical inspection of the vehicle? What economic and environmental benefits would be associated with the concept? 3. 4 Vehicle on a Driver and with Free NavigationVehicle on demand most closely resembles the use case, which, in the field of freight transport, is known as an autonomous, decentralized AGT/AGV system. A driver’s seat is not envisioned. However, in the use case outlined in Chap. 2 the vehicle can operate at speeds of up to 120 km/h and in unknown scenarios. [SEP] Justify:

Output: The text corroborates the claim by discussing the purpose and benefits of autonomous driving technology, specifically highlighting how the 'interstate pilot' reduces accidents and improves traffic flow. It mentions that the technology aims to relieve drivers from stressful situations and allows for safer driving, which aligns with the goal of reducing human error in transportation.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: Additionally, genera Clostridium, Enterococcus, Escherichia-Shigella, and Pseudomonas were positively correlated with viral titers in the nasal cavity, while genera Enterococcus, unclassified Erysipelotrichaceae, Escherichia-Shigella, Staphylococcus, and Pseudomonas were positively correlated with viral titers in trachea. Conversely, the Lactobacillus genus was negatively correlated with viral titers in the trachea. In conformation with our respiratory site-specific microbiota disruption hypothesis, Yildiz et al. [83] have also reported marginal effects of virus infection on lung microbiota (LRT) in a murine model. Furthermore, considering that active virus replication occurred between days 5–7 post infection [83], another important finding from this study is that microbiota disruption may persist even after virus clearance. The reduction in bacterial species richness was still observed in samples retrieved from the nasal cavity even at 14 days post infection. Innate immune responses, particularly via cytokine production related pathways, is a possible mechanism for the virus-mediated microbiota dysbiosis. This has been pointed out in several in vivo mouse and poultry studies [71, 85,86,87]. Therefore, virus-induced dysbiosis could potentially support the proliferation of pathobionts and opportunistic infections in poultry flocks [88, 89]. It is yet to be seen if probiotic formulations can restore microbiota homeostasis in the poultry respiratory tract, following viral challenge. Despite the very limited number of studies that have explored the effects of various intrinsic and extrinsic factors on the poultry respiratory microbiota, it is important to state that in the absence of well-designed a priori experiments, it is difficult to determine which of these factors exert the greatest effects. Much of the available data in the literature are confounded by several variables in their experimental design, hence the interpretation of these results needs to be treated with caution. For instance, multivariate regression models revealed that experimental factors including bird type, age, body site, and flock in the study by Taylor et al. [18] were only able to explain about 54% of the total sample variance. This suggests the existence of additional sources of microbial heterogeneity beyond those accounted for. [SEP] Justify:

Output: The text contrasts the claim by indicating that various factors, including viral infections and potentially diet, can disrupt microbiota composition. The mention of probiotic formulations aiming to restore microbiota homeostasis implies that changes, such as dietary adjustments, may influence microbiota composition. Moreover, the complexity of factors affecting microbial heterogeneity suggests that external influences like diet could play a significant role.


Input: Task: pass the claim using the given text. Claim: Fossil records provide critical evidence for understanding evolutionary processes. [SEP] Text: 402 [96] and concatenated using Geneious v10. 2 [92], with the default parameters. BI, ML, and MP methods were used to infer phylogenetic relationships. For BI analysis, PartitionFinder v2. 1. 1 [97] was used to estimate the best partitioning schemes and substitution models (Table S5). MrBayes v3. 22 [98] based on BI, was used to construct a phylogenetic tree. Carlo (MCMC) analyses were run for two million generations, sampling one tree every 100 generations and discarding the first 25% of trees as burn-in. The obtained trees were evaluated for convergence using Tracer v1. 7. 1 [99], with effective sample sizes (ESSs) > 200. For the ML analysis, IQ-tree v2. 1. 3 [100, 101] was used to estimate the best partitioning schemes and substitution models (Table S6), and the ML bootstrap support (MLBS) value of each branch was calculated with 1000 replicates. The MP analyses employed PAUP* 4. a168 on the XSEDE platform via the Cyberinfrastructure for Science () Gateway web server. All characters were treated as unordered and equally weighted, while branches with a minimum optimized length of zero were condensed [102]. The analysis utilized a heuristic search approach with tree bisection-reconnection (TBR) branch swapping. It generated 1000 replicates, employing random-addition-sequence methodology and allowing for the storage of up to 10,000 trees per replicate. From the retained most-parsimonious trees (MPTs), a strict consensus tree was derived. Bootstrap support values were calculated using bootstrap analyses [103] involving 1000 replicates. Each replicate consisted of 10 random-addition-sequence replicates, with a maximum of 100 trees saved per replicate. Fossil record and estimation of divergence timeData for the fossil record of the WCS were obtained from the literature, the ( and the Index ( BEAST v1. 10. 4 [104] was employed to estimate the divergence time. According to the most recent time-calibrated angiosperm phylogeny [29], the stem age of the WCS is constrained to 105. [SEP] Justify:

Output: The text does not address the claim directly. It discusses the methods used in phylogenetic analysis and mentions obtaining data for the fossil record but does not provide any evidence or insights regarding the importance of fossil records for understanding evolutionary processes.


Input: Task: corroborate the claim using the given text. Claim: Autonomous driving technology aims to reduce human error in transportation. [SEP] Text: There is some reason to believe that the “vehicle on demand” use case comes very close to the conception of autonomous vehicles in freight transport desired by companies in the industry: The local-language-speaking driver who is willing to undertake long interstate journeys with long periods of absence and irregular working hours for low pay is ever-more-difficult to find. Overtired truck drivers are the most common cause of severe accidents. Docking and maneuvering in tight delivery situations is always a tricky task for the driver. The use of automation technology could therefore be of great benefit. However, the approval of all scenarios for heavy trucks will take time, in particular due to safety concerns and required changes in the supply chain (see Sect. 18. 4). More likely is the realization of the interstate pilot without a driver and with free navigation between rendezvous points in the medium term, for example between rest areas on highways or between well-connected commercial zones. The likelihood of implementation of this use case could be increased through the following enhancement concepts:Safety concerns due to the lack of a driver on the fallback level could be mitigated by having separate highway entrances and exits for autonomous vehicles, as this would reduce encounters with other vehicles to a minimum. A dedicated lane for autonomous, coupled vehicles could probably avoid these concerns entirely. At the same time, such a dedicated lane could be the starting point for an extended concept with alternative drive technology, if the lane were, for example, outfitted with an overhead contact line for supplying electricity. The coupling of vehicles (platooning) would combine the initial concept of having a driver available in the lead vehicle as a backup with the extended concept in which vehicles drive autonomously without drivers and utilize the benefits of each concept. The platooning vehicles would be connected via a software system. Implementing the so-called electronic drawbar at high speeds would enable not only improved utilization of the road infrastructure, but above all reduced fuel consumption and emissions due to reduced wind resistance. Numerous tests have been carried out with the electronic drawbar since the mid-1990s [e. g. [SEP] Justify:

Output: The text corroborates the claim by discussing how automation technology could address the issue of overtired truck drivers, who are often the cause of severe accidents. It highlights the potential benefits of autonomous driving, such as reducing the risk of human error, particularly in freight transport scenarios where human drivers face challenges like long hours and fatigue. Additionally, the text describes proposed solutions like dedicated lanes and platooning, which further support the idea that autonomous technology aims to improve safety and reduce human error in transportation.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: The information provided here on select intrinsic and extrinsic factors that potentially influence the respiratory microbiota would be valuable for the design and execution of poultry microbiota studies with reproducible outcomes. Role of poultry respiratory microbiota in pathobiology and immune responsesThe avian mucosal surfaces are occupied by an abundant number of microbial communities that are in constant interaction with the host, other members of the community and the environment. A healthy balance of this tripartite relationship, especially in terms of compositional stability and diversity, ensures a healthy microbiota in humans [90]. Any compositional or functional alteration of this relationship is referred to as microbial dysbiosis, which is generally characterized by increased abundance of pathobionts [91]. Microbial dysbiotic conditions are implicated in several pathological conditions in avian species, including pathogen colonization, excessive inflammation, dysregulated immune responses, and severe disease conditions [33, 92]. The potential of the respiratory microbiota to influence viral infections, vaccine responses, secondary bacterial infections, and disease severity has also been reported [12, 93]. Consequently, the role of resident microbiota in the poultry respiratory tract on the host immune system and disease outcomes continues to be the subject of recent research [13, 94]. Information from studies of this nature could offer a better understanding of economically important avian diseases and zoonoses. Economically important avian respiratory diseases that are microbiota-exacerbated or linked to bacterial etiologies include but are not limited to Mycoplasma infection, infectious coryza, Colibacillosis and [10, 28, 71, 95,96,97,98,99] (Table 2). Under homeostatic conditions in the respiratory tract, commensal microbiota contribute to host immunity by inhibiting pathogen persistence and transmission via several means, including competitive exclusion, bacteriostatic activities, biofilm formation, quorum sensing, and others [100]. Conversely, under dysbiotic conditions, potential respiratory pathogens include Escherichia coli, Ornithobacterium rhinotracheale, Mycoplasma synoviae, Mycoplasma gallisepticum, Gallibacterium anatis, Avibacterium species, and Staphylococcus aureus [9, 33, 101]. [SEP] Justify:

Output: The text contrasts the claim by discussing the role of microbiota composition in health and disease, particularly highlighting how changes in the respiratory microbiota are implicated in various pathological conditions. It implies that alterations in microbial communities (which could stem from changes in diet or environment) affect immune responses and disease outcomes, contradicting the assertion that diet has no impact on microbiome composition.


Input: Task: pass the claim using the given text. Claim: Fossil records provide critical evidence for understanding evolutionary processes. [SEP] Text: AbbreviationsBP: Base pair BS: Bootstrap CTAB: Cetyltrimethylammonium bromide DNA: Deoxyribonucleic acid ESS: Size GC: Guanine and Cytosine GTR: Reversible IR: Inverted repeat ISC: Large single-copy MCMC: : MPT: Most-parsimonious tree PCG: Plastid protein-coding genes PP: Posterior probability rRNA: Ribosomal RNA tRNA: : Small single copy TBR: Bisection-reconnection WCS: Thewoody clade? in Saxifragales 9. 19. 77. 150. 5488. 22. 232. 4. Stuttgart, Germany: Borntraeger Science; 1892. 1959. 1981. 49. 25. 1997. 20. 10. 1111/jipb. 13415. . Discordance between nuclear and chloroplast phylogenies in the heuchera group (Saxifragaceae). Evolution. 1995;49(4):727–42. 50. 1012. 41. 57. 61. Fu D, Endress PK. Cercidiphyllaceae. In: editors. Flora of China. . St. Louis: Science Press, Beijing & Garden; 2001. p. 126. 2008. p. 315–317. Tang M-S, Tsai C-C, Yang Y-P, Sheue C-R, Liu S-H. A multilocus phylogeny of Daphniphyllum (Daphniphyllaceae). Environ. 2022;107:137–52. 1997. 29. 82. 70. 31. 56. 3544. 694. 70. 104. 67. 6. 66. 57. 8. 84. 68. 708. 12. 80. 7183. 74. 8. 70. 26. 66. 30. 2. 70. 412. 66. 63. 71. 14. 98. 983. Magallón S. From fossils to molecules: phylogeny and the core eudicot floral groundplan in Hamamelidoideae (Hamamelidaceae, Saxifragales). Syst Bot. 2007;32(2):317–47. 230. 64. 66. 75. 121. 22. 83. 72. 8. 8. 93. 43. [SEP] Justify:

Output: The text does not provide any direct information or insights about fossil records or their role in understanding evolutionary processes. Instead, it consists mostly of abbreviations and references to various scientific publications without relevant content relating to the claim.


Input: Task: corroborate the claim using the given text. Claim: Autonomous driving technology aims to reduce human error in transportation. [SEP] Text: the European projects “and II”, “Trains for the Environment ()”, “Cooperative mobility solution for supervised platooning ()”, the Californian “PATH Program”, the German “-Projekt: Entwicklung und Untersuchung des Einsatzes von elektrisch gekoppelten Lkw-Konvois auf Autobahnen”, and the Japanese “ITS Project” by the (NEDO)]. In these projects, multiple trucks or a convoy of lead trucks and following passenger cars safely drove at up to 90 km/h with a minimum gap of 4 m. The systems were based on surveillance by radar sensors, stereo cameras, three-dimensional maps and usually also data exchange with other vehicles. Previous trials were always conducted with a driver in the lead vehicle and with or without drivers for extended availability in the following vehicles. There are already ideas under consideration for a driverless lead vehicle. As a rule these projects build on proven existing technology: adaptive cruise control systems integrated in series-production vehicles serve to maintain the gaps between the vehicles. Data transmission between the lead and following vehicle is frequently conducted via wireless-transmission or infrared technology. The measured fuel savings and CO2-reduction potential differed depending on the selected vehicle-to-vehicle (V2V) communication (in “off-center” mode), the type and construction of the lead vehicle and following vehicles, the gap, the speed as well as the road and environmental conditions (surface, temperature, inclines, altitude). The difference was roughly 5 % for the lead truck and 10–15 % for the following passenger vehicles [18]. 3. 5 for Extended Availability—Follow-Me VehicleIn the use case presented in Chap. 2, the vehicle takes fully automated control whenever the situation is approved for that mode. The driver is at any time available and can resume vehicle control if necessary. In practice it is an extension of the interstate pilot in terms of approved situations and the permissible speed and is very similar to autonomous driving. This use case is only interesting from an economic perspective if the accompanying driver can pursue value-creating activities during the drive. The next delivery could be prepared or processed from an administrative standpoint during the drive itself. [SEP] Justify:

Output: The text corroborates the claim as it discusses various international projects focusing on automated vehicle operations. Specifically, it mentions how these projects involve systems that operate under conditions aimed at safety and efficiency, with an emphasis on surveillance technologies and communication systems between vehicles, which inherently seeks to minimize human error in driving scenarios. The reference to a driverless lead vehicle directly aligns with the objective of reducing human error in transportation.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: In addition to modifying the structural composition of the microbiota, another way in which AIV infection influences antiviral immune response in the host is by influencing microbiota diversity. There are conflicting reports on the effect of AIV infection on microbiota diversity in the literature. Kaul et al. [97] reported significantly higher microbial diversity (Beta diversity) in AIV-infected ferrets compared to uninfected ferrets. These microbial perturbations are facilitated by host antiviral responses, such as the induction of interferon [97]. In contrast, Chrzastek et al. [111] reported reduction in microbial richness and phylogenetic diversity in the colon microbiota of H9N2 AIV-infected birds. Similar reduction in species richness have been reported in the fecal microbiota of H5N1 AIV-infected swans [114]. In spite of this inconsistency related to the effect of AIV infection on microbial diversity in the literature, a simplistic definition of “low” or “high” levels of diversity and their relation to host antiviral immune responses may not be entirely correct. A closer look at the specific colonizers of the microbial community and the ecological niche occupied may afford better insight. For example, microbiota dominated by and Veillonella may signify specie richness. However, these taxa have been associated with increased AIV replication [71, 98]. It is also possible that the activities of this taxa differ depending on the ecological niche occupied. Also, they may increase AIV virulence in respiratory sites compared to the gut. Nonetheless, being the main site of infection, the effect of AIV infection on the respiratory microbiome requires more attention. Conversely, certain microbial species have demonstrated positive impacts on adaptive immune responses and antiviral responses. For instance, Alqazlan et al. [119] showcased the ability of specific Lactobacillus strains (such as L. salivarius, L. johnsonii, and L. reuteri) to induce immunostimulatory and antiviral responses against H9N2 AIV. [SEP] Justify:

Output: The text contrasts the claim by discussing how AIV (avian influenza virus) infection influences microbiota diversity and composition, which indicates that dietary or environmental factors may indeed impact the microbiome. The mention of microbial perturbations and varying reports on microbial diversity connected to infection implies that the microbiome can be altered by factors, including potential dietary changes.


Input: Task: pass the claim using the given text. Claim: Adaptive radiation explains the diversification of species in new environments. [SEP] Text: Skip to main content Explore journals Get published About BMC My account Search all BMC 19. 25 million years ago (Mya). This time represents the average between paleontological and molecular estimates, which place the origin of the crown group radiation, respectively, at 18. 5 and 20 Mya. Fig. 1Phylogenetic relationships within the Liolaemus radiation showing variation in body size (snout-vent length obtained by averaging male and female SVLs) across species (black bars, in mm). Clade colours indicate the eight main groups (or subgenera) within the genusFull size image Analyses of lineage diversificationAnalyses based on the time-calibrated phylogenetic tree were performed to quantify the evolutionary tempo and mode of diversification in Liolaemus, with focus on both lineage and body size diversity. To quantify historical rates of species accumulations (i. e. , tests of the prediction that diversification has slowed down over time following an early burst) we created a lineage through-time (LTT) plot implemented in the R package ‘ape’ [41]. For the LTT curve, we first implemented Pybus & Harvey’s [42] (MCCR) test. This analysis calculates the γ statistic for incompletely sampled phylogenies, by comparing the distribution of inter-node distances between the tree root and its temporal midpoint to the distribution of distances between the temporal midpoint and the tree tips [43]. Negative γ values indicate that inter-node distances between the root and the midpoint are shorter than the distances between the midpoint and the tips, and hence, that most branching events occurred earlier in the evolutionary history of the clade, a pattern consistent with a decline in the rate of species accumulation over time (i. e. , an ‘early burst’ model of diversification). When lineage diversification follows a constant rate process, the branching events are evenly distributed throughout the tree, with γ being normally distributed and with a mean of 0. Given that incomplete taxon sampling in a phylogeny increases type I error rates in diversification analyses, the MCCR test computes corrected γ distributions through simulations of phylogenies to the known clade size (~240 species in Liolaemus) under the null hypothesis of a constant rate pure-birth diversification process. [SEP] Justify:

Output: The text provides detailed information about analyses of lineage diversification, species accumulation, and phylogenetic relationships within a specific genus, Liolaemus. However, it does not directly address adaptive radiation or the role it plays in species diversification in new environments, making it irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Autonomous driving technology aims to reduce human error in transportation. [SEP] Text: Such vehicle concepts would also be conceivable for use in commercial passenger traffic, for example for activities in elderly care, the insurance industry, etc. , which involve documentation and administrative work. The “EmiL” concept study of a partially autonomous delivery vehicle in 2011 can be regarded as a sort of preliminary stage of development before full automation [19]. In this concept, the delivery person does not need to continually get in and out of the vehicle, but can instruct the vehicle via mobile phone to drive next to him at walking speed (follow-me function). For all unknown situations (e. g. merging situations, intersections), there is the additional DriveStick mode in which the vehicle can be driven at up to a speed of 6 km/h. The use of a local wireless-connection precludes signal interruptions that are feared and can indeed occur with GPS connections. The research project determined a time-saving of about 40 min over a one-day delivery period. The typical injury risk of twisting or rolling an ankle when getting out of the vehicle is also reduced. 3. 6 Valet Parking—Valet DeliveryValet parking refers to the use case in which the autopilot independently navigates the vehicle to a previously assigned parking spot. The concept presented in Chap. 2 assumes that this could be possible in the public sphere at speeds of up to 30 km/h. One example could be autonomous driving from a driver’s place of residence to a defined parking spot. This use case is scarcely conceivable in the context of freight transport, however, as there are truck-parking locations rarely connected via the secondary road network. Much more likely is a scenario in which the autopilot would take over in tight inner-city areas and industrial and retail delivery zones not designed for large trucks and park or dock the truck independently. This could prevent expensive car damages to occur. The driver would be relieved of stressful driving tasks, which would be particularly advantageous in light of the driver’s remaining responsibility for long, exhausting highway drives. Valet delivery could also help drivers comply with legal rest times if the “last mile” could be conducted without their assistance. Another potential use case could be delivery to construction sites. In major construction jobs, trucks are increasingly held in so-called waiting zones in the vicinity of the construction site. [SEP] Justify:

Output: The text corroborates the claim by detailing various use cases for partially autonomous vehicles that highlight the reduction of human error and the alleviation of stressful driving tasks. For example, it states that the driver would be relieved of stressful driving tasks, which would be particularly advantageous given the driver’s remaining responsibility for long, exhausting highway drives. Additionally, the concept of 'valet delivery' suggests a scenario where the vehicle can operate without driver assistance, thereby minimizing the risk of accidents associated with human error.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: These responses encompass the activation of interferon-stimulated gene (viperin) and the robust expression of cytokines in cells of the ceca tonsils, including T-helper (Th)1 type cytokines (interleukin [IL]-2, IL-12, and IFN-γ), pro-inflammatory cytokines (IL-1β and IL-6), and an immunoregulatory cytokine (IL-10). Moreover, a combination of Lactobacillus species, comprising Lactobacillus salivarius, L. johnsonii, L. reuteri, L. crispatus, and L. gasseri, has also been shown to enhance both cell- and antibody-mediated immune responses against H9N2 AIV [78]. This beneficial effect is particularly pronounced when co-administered with synthetic CpG oligodeoxynucleotides (ODN) 2007. Avian mycoplasmosisis a chronic infectious respiratory disease that affects poultry of all ages. The economic consequence of this disease includes poor hatchability, reduced egg production, poor weight gain and egg production [120]. The etiological agent of this disease is the pathogenic bacterium, Mycoplasma gallisepticum (MG), which is commonly isolated on most poultry farms. This pathogen can be spread both vertically and horizontally and can cause severe inflammatory responses and immune dysregulation in birds [120, 121]. Current management tools available to curb MG infection on farms include sourcing birds from breeding stock that are certified as healthy, implementing rigorous biosecurity practices, administering vaccinations, and delivering antimicrobials to infected birds [122, 123]. Although the use of antibiotics like fluoroquinolones and macrolides is a popular approach, there is a growing concern related to the development of antimicrobial resistance in this pathogen [124, 125]. By combining both 16S rRNA sequencing methods and an antibiotic-induced microbiota depletion protocol, Wang et al. [10] were able to provide insight into the role of the respiratory microbiota on MG infection in layer chickens. The findings of this study revealed that MG infection induces a distinctive shift in the microbiota community. Specifically, there was a significant decrease in the relative abundance of bacteria such as Staphylococcus, Lactobacillus, Weissella, and Butyricicoccus in their study. [SEP] Justify:

Output: The text contrasts the claim by highlighting that MG infection induces a distinctive shift in the microbiota community, indicating that factors such as infection can affect microbiome composition, which implies that dietary changes could similarly impact it. The mention of 'a significant decrease in the relative abundance of bacteria' further supports the argument that microbiome composition can change due to different influences, contradicting the claim that diet has no impact.