Input: Task: pass the claim using the given text. Claim: Phonetics analyzes the sounds of human speech. [SEP] Text: According to two major groups of parts of speech, forty-seven content words were written in bold face, while fifty-one function words, as well as plural morphemes (-s, raindrops, colors, ends, friends) and inflectional morphemes (-s, strikes, finds), were denoted in plain type (see Benner, 2020; Nordquist, 2020; O’Shea, 2013 for group classification). 2. 2. Data collection and analysis Data for analysis were collected in three steps: recording of the rainbow passage by the participants at home using their mobile phones; recognition of the recording by a speech recognition application, Speechnotes ( and evaluation of the recording by two native Canadian English-speaking raters. The application uses Google’s speech-recognition engines with expected accuracy levels higher than 90%, which was proved by the two Canadians’ recordings. Statistical analyses of the recognition rate and human raters were conducted using and R software (R Core Team, 2020). To avoid the reader’s parsing errors without knowing the context of the passage, the author asked the participants to prepare for the task by listening to the native pronunciation of the passage using Papago (Naver, 2020) and by practicing it sufficiently in advance (Levis, 2011). As mentioned in the introduction, there might have been some evaluation problems regarding authenticity in read speech. However, we decided to use the passage to ensure comparable recordings in clear speech mode. If we used free speech, recognition rates and intelligibility levels on speech recordings of different sizes, word choices, or syntactic structures might not be comparable among various participants. Further studies of both free and read speeches are desirable to pursue any findings related to the comparability issue. The original recordings of the participants were converted to the same file format, i. e. , 16 bit mono at a 44. 1-kHz sampling rate, and normalized to the peak of the sound files. Some speech segments with low intensity were boosted by SoundStudio on a Macintosh computer to render the sounds sufficiently loud for the speech recognition application and the human raters. Then, the sound files were played on the computer, and the recognized output texts were transcribed by the speech recognition application on a Note 10 in a quiet room. The recognition procedure was applied twice per each speaker in a row. There were slight differences in the transcribed output texts. [SEP] Justify:

Output: The text does not address phonetics nor does it mention the analysis of sounds of human speech. Instead, it focuses on data collection and analysis procedures involving speech recognition technology, highlighting recording methods and statistical evaluation without relating to the claim about phonetics.


Input: Task: corroborate the claim using the given text. Claim: Crop rotation helps prevent soil depletion and pest buildup. [SEP] Text: Planting of flowers as pollen and nectar sources may also provide necessary food for parasitic fly and wasp adults. This would include the spraying of bacteria or virus as well as releases of parasites and predators. Importation is bringing exotic parasites and predators into the country for release against pests. This tactic is especially useful when combatting imported pests. Cultural controlWe finally come to the cited topic of this paper, cultural controls of insect pests of urban ornamentals. A useful definition of cultural control is the manipulation of the physical environment so as to reduce the survivorship of a pest. In essence, any changing of the environment or habitat which makes it difficult for a pest to survive and reproduce falls in this category. Crop rotation, sanitation and resistance were picked because these are claimed, almost exclusively, for use in field crops and vegetables. However, these controls are used and could be more useful if modified for urban arborists. It would be prudent to state that the following suggestions have not been generally investigated in a scientific manner and the recommendations often do not fit within the norm for arborist training. Crop RotationCrop rotation is the switching from one species of crop to another. This time honored agronomic practice has generally been ignored by growers of ornamental plants. However, if we consider that trees are merely a crop which is planted, matured, harvested and replanted, the only difference is in the time of maturation. Also, if the trees had continuing pest problems in the past, why replant with the same type of trees? Why not go with a new species? Christmas tree growers in Pennsylvania are having a similar problem. New growers who planted their acreage with Scots pine usually didn’t have severe pest problems until a few years before harvest. However, after harvest, if the land was replanted in Scots pine the pest problems were immediate and continuing. Some growers have recently experimented with crop rotation and have had good success. On land that will only support pine, these growers have planted a cover crop of grass or buckwheat for a year before replanting with trees. Other growers have land which will support spruce or fir and have successfully rotated to these species. Another anticipated problem with urban tree crop rotation is the American ideal of “biggest and oldest tree. ” Let’s face facts, the urban environment is not the place to grow the biggest and oldest trees. [SEP] Justify:

Output: The text corroborates the claim by discussing the benefits of crop rotation in managing pest problems and the health of trees. It mentions that crop rotation has been experimented with by some growers, who have found success in preventing ongoing pest issues by planting different species rather than replanting the same type of trees. Moreover, the text illustrates the concept of crop rotation as a way to manipulate the environment to reduce pest survivorship, supporting the idea that rotating crops can aid in preventing soil depletion and pest buildup.


Input: Task: contrast the claim using the given text. Claim: Every individual responds the same way to environmental stimuli. [SEP] Text: The left panels show: up, ommatidium lens; middle, basal cone/pigment cell layer; down, R1-R7 photoreceptor rhabdomeres tips during and after flash stimulation. The right panels show the cross-correlation time series of these high-speed videos: up, the corneal lens and the upper ommatidium structures were essentially immobile), and normally remained so throughout the recordings; Middle, cone cells that connect to the rhabdomere tips with adherens junctions (Tepass and Harris, 2007) showed clear light-induced movements; down, R1-R7 rhabdomeres moved half as much as the cone cells above. The high-speed video rate was 500 frames/s. Video playback slowed down and down-sampled to reveal the contractions, which otherwise would be too fast to see with a naked eye. Tables 10. 7554/eLife. 26117. 050 10. 7554/eLife. 26117. 057 Light- PointPeak1 wavelength (nm)Peak1 intensity (106 photons/s)Peak2 wavelength (nm)Peak2 intensity (106 photons/s)No. 14482. 7205712. 805No. 24521. 7905702. 818No. 34482. 6185652. 900No. 44511. 8405763. 020No. 54512. 5705753. 710No. 64512. 2145723. 640No. 74521. 4305752. 020No. 84462. 2035702. 990No. 94531. 4655712. 350No. 104513. 3005785. 100No. 114531. 8775753. 080No. 124551. 7635753. 020No. 134512. 3345753. 440No. 144512. 0095762. 634No. 154542. 4005684. 480No. 164522. 3905724. 165No. 174553. 1905663. 010No. 184521. 9905783. 320No. 194551. 9585783. 336No. 204541. 7455692. 670No. 214502. 6425732. 314No. 224529. 52057213. [SEP] Justify:

Output: The text contrasts the claim by providing details about differential responsiveness of photoreceptor cells in the sensory structures. Specifically, it mentions that 'R1-R7 rhabdomeres moved half as much as the cone cells above,' which indicates that not all cells respond identically to the same environmental stimuli (flash stimulation in this case). This suggests variability in response among different components of the visual system.


Input: Task: pass the claim using the given text. Claim: Phonetics analyzes the sounds of human speech. [SEP] Text: The recognition rate was calculated by determining the percentage of correctly recognized words, which occurred in either the first or second output texts. The recognized words were also divided into forty-seven content words and fifty-one function words to examine any group differences in the word types. Both the content words with and without the morphemes were counted as correctly recognized words in this paper. The “table” function in R was used to collect the categorical frequency distribution of unrecognized words or general patterns of incorrect recognition. The two native raters listened to the recordings and evaluated the read speech of the thirty-one participants using System (IELTS) band criteria for pronunciation (IDP Education Canada, 2020). The speaking section in IELTS assesses the use of free spoken English through an examiner’s individual face-to-face interview on test takers’ homes, families, and interests in Part 1, and the test takers may write down their own thoughts on an assigned topic for a minute and answer them in two minutes in Part 2 and discuss them further in Part 3. The level is determined by the band descriptors from 0 to 9 for fluency and coherence, lexical resource, grammatical range, accuracy and pronunciation. The scoring description for a very good user of band 8 reads a wide range of pronunciation features and has an easy understanding throughout, as well as minimal effect of the L1 accent on intelligibility. The raters were instructed to evaluate the participants’ recordings using the full range focusing only on pronunciation intelligibility of the read speech. The raters watched a 15-minute sample video interview of five test takers in five bands: 5. 5, 6. 5, 7. 5, 8. 5, and 9. In this way, they could avoid confusion regarding the intelligibility band reported in Kang & Ahn (2013). 3. Results and Discussion 3. 1. Speech recognition rates Table 1 lists basic statistics of speech recognition rates by the speech recognition application. To facilitate the readers’ understanding, both the number of correctly recognized words and their percentages of the total number of words in the rainbow passage are reported in the table. We use mostly percentages in the discussion. As described in the previous section, the total number of words in the passage was 98: 47 content words and 51 function words. The grand average percentage of correctly recognized words was 77. 7%, i. e. , 76. [SEP] Justify:

Output: The text is irrelevant to the claim regarding phonetics as it focuses on a study evaluating speech recognition rates and does not directly reference the analysis of speech sounds, which is the central aspect of phonetics.


Input: Task: corroborate the claim using the given text. Claim: Hydroponics allows for soil-less farming, using nutrient-rich water instead. [SEP] Text: Javascript is disabled in your browser. Please enable Javascript to view PeerJ. Related research -nutrient estimator: distributing nutrient solution in hydroponic plants based on plant growth View 10. 7717/peerj-cs. 1871 Published 2024-02-23 Accepted 2024-01-22 Received 2023-09-29 -Time and hydroponic, Nutrient estimator, Mask R-sensors, Micro nutrients, Macro nutrients, Region proposal network Copyright © 2024 Sangeetha and This is an open access 2024. Automatic nutrient estimator: distributing nutrient solution in hydroponic plants based on plant growth. PeerJ 10:e1871 The authors have chosen to make the review history of this 97. 5% accuracy for the first 5 weeks with 1,715 ppm of nutrition ingestion, identifying the vegetative state. The flowering stage is identified with 97. 5% accuracy in the 6–9th week with 2,380 ppm of nutrition consumption, and the fruiting location is determined with 99. 4% accuracy in the last 10–15th week with 2,730 ppm of nutrition consumption. world’s population is projected to increase from 6. 8 billion today to 9. 1 billion by 2050. This growth will necessitate a 25% increase in food production compared to the current levels (FAO, 2022a). According to research conducted by the FAO, meeting this demand and simultaneously addressing issues such as hunger, poverty, efficient management of finite natural resources, and adaptation to climate change will pose significant challenges for global agriculture in the upcoming decades. (FAO) (FAO, 2022b) projects that in India, more than 189 million people may receive less food in terms of quantity and quality for healthy growth by 2020. In India, the population is increasing rapidly, but at the same time, the percentage of agricultural land is decreasing. At the same time, inadequate water resources, fewer rainfalls, increased expenses, and sudden disasters decreased farmers’ interest in farming. As a result, many of them have transitioned into the real estate sector to seek higher profits within a shorter timeframe (Shirsekar et al. , 2021). Hydroponics is a branch of hydroculture that is the most suitable explanation for these difficulties. Hydroponics farming (Tagle et al. [SEP] Justify:

Output: The text supports the claim by indicating that hydroponics is a branch of hydroculture, which directly relates to the concept of soil-less farming. The mention of nutrient solutions and their distribution in hydroponic systems further aligns with the definition of hydroponics as using nutrient-rich water for plant growth instead of soil.


Input: Task: pass the claim using the given text. Claim: Every individual responds the same way to environmental stimuli. [SEP] Text: on apatosaur neck combat Upchurch, Mannion and Taylor (2015) on Haestasaurus becklesii Kraatz, Sherratt, Bumacod, and Wedel (2015) on rabbit skulls Taylor (2014) on quantifying neck cartilage Foster and Wedel (2014) on the Farke, Cifelli, Maxwell, and Wedel (2014) on et al (2014) on the perforating branch of the peroneal artery Taylor (2014 for 2004) on dinosaur diversity Wedel and Taylor (2013b) on caudal pneumaticity Taylor and Wedel (2013b) on neck cartilage Wedel and Taylor (2013a) on sauropod neural spine bifurcation Taylor and Wedel (2013a) on sauropod neck anatomy Wedel (2012) on long nerves of sauropods Yates, Wedel, and Bonnan (2012) on prosauropod pneumaticity Taylor, Hone, Wedel and Naish (2011) on sexual selection of sauropod necks Taylor, Wedel and Cifelli (2011) on (2010) on the history of sauropod research Taylor (2009) on the inevitability of electronic publishing of nomenclatural acts Taylor (2009) on Brachiosaurus and Giraffatitan Taylor, Wedel and Naish (2009) on neck posture Upchurch, Martin, and Taylor (2009) on Cetiosaurus nomenclature Wedel (2009) on air sacs Taylor and Naish (2007) on 100% totally real brachiosaurids Brachiosaurus caudal cervical collections diplodocids Diplodocus dorsal Giraffatitan goofy mounts museums navel blogging necks open access papers by SV-POW! [SEP] Justify:

Output: The text is irrelevant to the claim as it consists of a list of references and studies primarily related to sauropod anatomy and handling of neck features. There is no discussion or evidence provided regarding individual responses to environmental stimuli, therefore it does not corroborate or contrast the claim.


Input: Task: pass the claim using the given text. Claim: Phonetics analyzes the sounds of human speech. [SEP] Text: 2 of 98 words. Had we used a different recording passage, the result would have varied. The correctly recognized percentage of all of the words ranged from 63. 3% to 87. 8%. The moderate rate generally indicates the proficiency level of the participants as intermediate or higher. It also suggested the usefulness of the recognition application as an evaluation tool. Interestingly, the correctly recognized percentage of the function words was greater than that of the content words by approximately 8% points. Table 1. Statistics of speech recognition rates. The number indicates correctly recognized words, followed by the percentage in parenthesis. SD indicates the standard deviation; Max, the highest instance; Min, the lowest instance words (%) Function words (%) All words (%) Average 34. 6 (73. 6) 41. 6 (81. 5) 76. 2 (77. 7) SD 4. 1 (8. 6) 2. 6 (5. 1) 6. 1 (6. 3) Max 41 (87. 2) 45 (88. 2) 86 (87. 8) Min 35 (68. 6) 27 (57. 4) 62 (63. 3) percentage of the standard deviation of all correctly recognized words was approximately 6%. There was a 3. 5% difference in the deviation between the content and function word groups. The content word group showed lower recognition and wider deviation, which might be related to some pronunciation errors of specific consonants or vowels by the participants. Conversely, the range of correctly recognized function words extended much wider than the content words. We examine frequently unrecognized words and pronunciation errors in the section below. The higher recognition rate of the function words might be related to hyperarticulation of the participants without applying such general phonological processes as resyllabification or vowel weakening to their read speech. The participants were divided into high- and low-level groups greater and less than 79% of the recognition rate: fifteen high-level and sixteen low-level participants. Table 2 shows the group statistics of speech recognition rates of the content and function words. Table 2. Statistics of speech recognition rates in the high- and low-level groups. The number indicates correctly recognized words, followed by the percentage in parenthesis. SD indicates the standard deviation; Max, the highest instance; Min, the lowest instance Content words (%) Function words (%) All words (%) 37. 7 (80. 1) 43. 5 (85. 2) 81. 1 (82. [SEP] Justify:

Output: The text does not address the claim regarding phonetics analyzing the sounds of human speech. Instead, it focuses on speech recognition rates, the performance of participants in recognizing words, and the effects of different types of words (function vs. content) on recognition rates. The analysis relates to speech recognition rather than phonetics as a field of study.


Input: Task: corroborate the claim using the given text. Claim: Hydroponics allows for soil-less farming, using nutrient-rich water instead. [SEP] Text: , 2018) is an intelligent way of growing crops that yields high-quality organic plants in a limited space without using soil and does not expose them to external disasters, and not causing any environmental pollution. The hydroponic food production method is becoming more popular for cultivating crops, especially for urban people who can grow plants on balconies or rooftops (Kaewwiset & Yooyativong, 2017). The hydroponic food production method of cultivation, referred to as “soilless culture” (Resh, 2022), uses water or nutrient solutions as the growing standard. Possibility of using land that is unsuitable for conventional agriculture, such as dry and degraded terrain. The ability of plants to adapt to shifting weather patterns. Cultivation is possible all year. Reduced need for labor-intensive operations such as weeding and soil preparation. These are the method’s primary advantages (Gumisiriza et al. , 2022). There is debate about whether hydroponic farming is more active than conventional farming (Atikah & Widyawati, 2021; Lee & Lee, 2015). Hydroponics agriculture has become a revolution in many countries and is slowly spreading in India. It has proved that it can ultimately grow pesticide-free crops with 95% less water and consume reduced nutrients compared to conventional agriculture. Six different methods of growing hydroponics include deep water culture, wick system, nutrient film technology, ebb and flow systems, drip systems, and aeroponics. It can choose any growing medium except soil like coconut pellets, perlite gravel, rockwool, or sand, or it can be any nutrient explanation. Plants are grown either horizontally or vertically based on space availability (Nursyahid et al. , 2021). In our system, we used deep water culture to grow plants, as shown in Fig. 1. Figure 1: Deep water culture for hydroponics. Download full-size image DOI: 10. 7717/peerj-cs. 1871/fig-1 The entire method for a vertical farming controlled environment comprises three significant steps. The first step is about intelligent sensors for monitoring several parameters, including air density, humidity, light intensity, temperature, CO2 levels, oxygen levels, water inflows, and recording pH and EC values. The second step covers caring for the plants under a controlled environment and regulating all the above parameters in specific ranges or threshold values. [SEP] Justify:

Output: The text corroborates the claim as it explicitly describes hydroponics as a 'soilless culture' that utilizes 'water or nutrient solutions as the growing standard.' Additionally, it emphasizes the advantages of hydroponics, which include the ability to grow crops without using soil, confirming the core aspect of the claim.


Input: Task: contrast the claim using the given text. Claim: Every individual responds the same way to environmental stimuli. [SEP] Text: solstitialis populations sampled around the globe, indicating that the species invasive success is not due to changes in genome size or ploidy level. in ploidy level have been reported to be important for the invasive success of some plants species (et al. , 2011), by altering morphological, physiological and ecological parameters which can confer hybrid vigor, stress resistance, competitive advantages, or increased phenotypic plasticity, like in the case of the tetraploids of Centaurea stoebe L. (Hahn, Buckley & Müller-Schärer, 2012). Additionally, there are a series of associated “genome size constrained traits”, related mostly to reproduction and dispersal, which dictate the ecological niche a species can access (et al. , 2011). In contrast, several studies support the hypothesis that a smaller genome can contribute to some species invasive potential by boosting early plant growth and enhancing competitive ability (Bennett, Leitch & Hanson, 1998; Grotkopp et al. , 2004; Beaulieu et al. , 2007; Lavergne, Muenke & Molofsky, 2010; Suda et al. , 2015). For instance, Phalaris arundinacea L. (reed canary grass, Poaceae) in the USA underwent a quick and significant reduction in genome size compared to the native European genotype, which was correlated with some advantageous phenotypic effects and enhanced aggressiveness (Lavergne, Muenke & Molofsky, 2010). A list comparing the ploidy level of 128 worst invasive plant species worldwide, was recently made available by et al. (2011), indicating that a quarter of them possess at least two different ploidy levels. An interesting example is C. stoebe (spotted knapweed) which occurs both as a diploid and tetraploid, with only the latter cytotype becoming invasive in the Western parts of the USA (Mráz et al. , 2011). However, for many invasive species, ploidy levels and genome size are unknown or have not been thoroughly investigated. Centaurea L. is one of the most species rich genera in the Asteraceae (Bremer, 1994). species have been introduced into new non-native regions, where many of them have become invasive. [SEP] Justify:

Output: The text contrasts the claim by suggesting that different ploidy levels and genome sizes can lead to varying responses to environmental stimuli among species. For instance, it discusses how morphological, physiological, and ecological parameters can confer different advantages and stress resistance based on genomic traits, indicating that individuals might not respond uniformly to the same environmental conditions.


Input: Task: pass the claim using the given text. Claim: Phonetics analyzes the sounds of human speech. [SEP] Text: 8) SD 1. 8 (3. 8) 1. 5 (3. 0) 2. 1 (2. 2) Max 41 (87. 2) 45 (88. 2) 86 (87. 8) Min 35 (74. 5) 40 (78. 4) 78 (79. 6) 31. 6 (67. 2) 40. 0 (78. 4) 71. 6 (73. 0) SD 3. 5 (7. 4) 2. 1 (4. 1) 4. 9 (5. 0) Max 37 (78. 7) 43 (84. 3) 77 (78. 6) Min 26 (55. 3) 36 (70. 6) 62 (63. 3) table indicates that the two groups are different in basic statistics. The average percentage of the high-level group is 82. 8%, while that of the low-level group is 73. 0%. The difference between the two groups amounts to 9. 8%. From the maximum and minimum rates we determine the range of each group from 8. 2% to 15. 3%, respectively. Both the high- and low-level groups demonstrate higher recognition rates of the function words by 5. 1% and 11. 2%, respectively. The result might be related to the reliability of the recognition algorithm and recording devices. The recordings were made by the participants with their own mobile phones in various settings. Further studies might find it interesting to compare the results of sound-proof booths or individual recording settings. The standard deviation of the high-level group was almost half of the deviation of the low-level group. The difference might be related to the pool of the participants and the selection of the passage in this study. Different pools of each group and level of the passage would lead to various patterns of difficulties with the content and function words. Table 3 illustrates the percentage of correctly recognized words by sentence type. One can note that the recognition rates vary by the size and order of the sentence. The best recognition occurs in the last sentence, while the third sentence lists the worst recognition rate. The last phrase in Row 15 records 100% recognition. Among the rows in the third sentence, we found 53. 5% recognition in Row 8. The word “path” lists many unrecognized cases, and in Row 4, for the first sentence, the phrase “form a” listed an almost comparable low rate of 58. [SEP] Justify:

Output: The text does not directly address the nature of phonetics or its focus on analyzing the sounds of human speech. Instead, it provides statistical data on recognition rates of words in different contexts and groups, which is not relevant to the claim about phonetics.


Input: Task: corroborate the claim using the given text. Claim: Hydroponics allows for soil-less farming, using nutrient-rich water instead. [SEP] Text: The last step is crucial for monitoring plant disease detection, weeds detection, pollination, prediction of nutrients mixture along with plant growth maturity stage identification, and messaging complete crop information through smart phone to inform the farmer about changes and for good yielding (Saputra, Irawan & Nugraha, 2017). The fundamental factors which affect a plant’s growth include pH, temperature, CO2, and EC of the water in the system. Four primary sensors control the environment in our hydroponics system. They are DHT11 (temperature and humidity), ultrasonic sensors (water flows), EC sensors (nutrient dissolvability), and pH sensors (acidity of nutrient solution). For these factors, we use an Arduino UNO to communicate and monitor whether or not the readings are in the given threshold range. Instead of soil, hydroponics is fed with nutrient solution added to the normal RO water. Hydroponics needs a varying number of macronutrients and micronutrients throughout its life cycle. Macronutrients are called primary nutrients and are crucial for the plant’s health; these include nitrogen (N), phosphorus (P), and potassium (K), which are available from Ca (NO3)2 (calcium nitrate), KNO3 (potassium nitrate), and KH2PO4 (mono-potassium phosphate). In addition to the NPK mixture, micronutrients are also needed for plants that, include calcium (Ca), manganese (Mn), zinc (Zn), boron (B), iron (Fe), molybdate (Mo), chlorine (Cl), magnesium (Mg), copper (Cu) and sulfur (S). Proper nutrients, like nitrogen, phosphorous, potassium, etc. , are essential for plant development. Estimating ratios of NPK solution is a significant step that helps in high productivity (Shirsekar et al. , 2021). In hydroponic systems, plant growth and efficiency mainly depend on two main features, EC and pH values, that regulate plant nutrient uptake. We use a pH meter to measure the pH of the nutrient solution. If the pH value measured below seven, that shows acidic, whereas above seven shows basis or alkaline of explanation. The threshold range of pH values of hydroponics plants is mostly from 5. 5 to 6. 4. [SEP] Justify:

Output: The text corroborates the claim by explicitly stating that 'instead of soil, hydroponics is fed with nutrient solution added to the normal RO water.' This directly supports the idea of hydroponics as a method of soil-less farming that utilizes nutrient-rich water, aligning perfectly with the claim.


Input: Task: contrast the claim using the given text. Claim: Every individual responds the same way to environmental stimuli. [SEP] Text: For instance, the US Weeds list (2017), includes no fewer than 13 taxa, but ploidy level for many of these is unknown or uncertain. In particular, C. solstitialis is a Eurasian native annual herb which was introduced into the Americas and Australia during the last two centuries (Barker et al. , 2017) and became an impactful invader in the former case. In the invaded ranges, C. solstitialis forms dense stands that displace native plants species and reduce considerably livestock grazing capacity and forage value (Eagle et al. , 2007). It alters ecosystem functions by depleting soil water and nutrients through an extensive root system (DiTomaso, 2000), and can cause a neurological disorder in horses similar to human Parkinson (Chang et al. , 2011). As an economically important plant, the species has been the subject of intensive research, and significant differentiation between native and non-native ranges have been reported for plant size (Eriksen et al. , 2012; Graebner, Callaway & Montesinos, 2012; García et al. , 2013; Dlugosch et al. , 2015), growth rates (Graebner, Callaway & Montesinos, 2012), germination (Hierro et al. , 2009), competitive ability (Montesinos & Callaway, 2017), and reproduction (Montesinos, Santiago & Callaway, 2012), among others. Such changes suggest diverging local adaptation occurring among native and non-native ranges, and hypothetical changes in genome size and ploidy level could be potentially responsible for at least some of the observed trait-shifts. Until now, only three genome size estimates were available in the literature for C. solstitialis: two from the native range (Bulgaria: 1. 74 pg/2C, one accession, in Bancheva & Greilhuber, 2006; and Croatia: 1. 95 pg/2C, five accessions, in Carev et al. , 2017) and another from an invasive population in western USA: 1. 66 pg/2C, thirty accessions (Miskella, 2014). Based on these few studies, C. solstitialis had been reported to be diploid (Dlugosch et al. , 2013; Rice et al. , 2015) with 2n = 2x = 16 chromosomes. [SEP] Justify:

Output: The text contrasts the claim by describing how the invasive plant species C. solstitialis shows significant differentiation in traits such as growth rates and competitive ability between its native and non-native ranges. This suggests that individuals from different environments may adapt differently to local conditions, indicating that not every individual responds the same way to environmental stimuli.


Input: Task: pass the claim using the given text. Claim: Phonetics analyzes the sounds of human speech. [SEP] Text: 1%, in which the two words were recognized as one word like the English word “former”. We discuss a few cases of one-word recognition for a pair of words in the following section. In contrast, the first sentence records 72. 8% recognition. The low recognition rate at the beginning might be related to abrupt adaptation of the speech recognition application itself. There used to be a short silence period at the beginning of the recording so that the application had sufficient sound data to immediately begin the recognition process. From these results, we could say that the recognition could vary depending on the composition of the content and function words in each given sentence. To perform a meaningful evaluation of the participants’ speech, we might have to examine controlled or balanced components of the vocabulary from both free and read speech (Levis, 2011). Table 3. Statistics of speech recognition rates by the sentence. The number indicates the percentage of correctly recognized words within each sentence Sentence no. Content words (%) Function words (%) All words (%) 1 182 (73. 4) 230 (71. 9) 412 (72. 8) 2 186 (84. 7) 137 (89. 0) 323 (86. 9) 3 196 (75. 0) 240 (69. 7) 436 (62. 8) 4 187 (72. 4) 127 (78. 5) 314 (74. 7) 5 56 (60. 2) 103 (83. 1) 159 (73. 3) 6 263 (85. 2) 455 (92. 7) 718 (90. 0) Table 3. 2. Frequency counts of unrecognized words by group level and word type An examination of the unrecognized words might be necessary to diagnose and remedy the talker’s pronunciation errors. Table 4 lists the frequency counts of unrecognized content and function words. Table 4. List of high ranking content and function words in the frequency counts of unrecognized words Content words (%) words (%) 29 The 63 Is 28 A 44 Form 26 These 25 Path 24 Its 24 Ends 22 When 20 Arch 18 There 19 Take 18 With 13 Man 15 Above 12 Two 15 But 11 Prism 14 And 8 People 13 Of 7 Shape 12 They 7 High 11 His 6 Sunlight 11 Ever 4 According 10 Many 4 Round 10 No one 4 content word “looks” ranks as the most frequently unrecognized instance, followed by the word “is”. [SEP] Justify:

Output: The text is irrelevant to the claim as it focuses on speech recognition rates and the evaluation of word recognition in sentences, without addressing the study of the sounds of human speech, which is central to phonetics.


Input: Task: corroborate the claim using the given text. Claim: Hydroponics allows for soil-less farming, using nutrient-rich water instead. [SEP] Text: The DAQ program, written in Arduino software, was intended to collect and store data from six hydroponic parameters. Tembe, Khan & Acharekar (2018) suggested a hydroponics technique in 2018 to meet humans’ food requirements. They put the pH probe module and the light spectrum for hydroponics in place. The hydroponics idea can be applied in areas that are experiencing drought. Hydroponic plants can produce a higher yield and quality with less water consumption. It is not affected by the environment in the hydroponics system, and crops can be grown all year. The foremost disadvantage of a hydroponic system is the higher initial setup cost and the requirement to implement automatic monitoring equipment. Likewise, it requires constant supervision from the farmer. Power outages must be resolved manually in Sihombing et al. (2018) recently established hydroponic organization that only procedures the temperature of the nutrient clarification and the water level. A smartphone can be used to monitor the system. The method developed by Belhekar et al. (2018) and Jaimes et al. (2019) measures the system’s relative humidity, temperature, electrical conductivity, pH, and water level. Farmers are alerted to situations like systemic nutrient imbalances by the data submitted to a database. Monitoring the hydroponic atmosphere is the only function of the system. Therefore, the system is without actuators and depends on the farmer to control occurrences (Belhekar et al. , 2018). et al. (2019) can add rainwater to the design and regulate pH levels. The volume and velocity problem of data generated in a hydroponic system is addressed by Chaiwongsai (2019) using data fusion. Data fusion is a technique that merges (fuses) information from many sensors to provide a more accurate result. Moreover, data fusion lessens network transfers, which lowers traffic and energy use. The authors suggested a control and management system for tropical hydroponic horticulture. The system keeps track of data on the state of the power, temperature, humidity, water level, pH, and EC, which are then sent over the internet to a remote database. Users can access a mobile application to verify the hydroponic sensor’s status. A two-tier network of sensors (including data fusion and SI sensors) makes up the system (DFi). [SEP] Justify:

Output: The text corroborates the claim by detailing various aspects of hydroponics, which is clearly a method of soil-less farming that uses nutrient-rich water. It discusses how hydroponic systems can function in places experiencing drought, highlighting their advantages over traditional agriculture, such as higher yields and lower water consumption, all of which align with the definition provided in the claim.


Input: Task: contrast the claim using the given text. Claim: Every individual responds the same way to environmental stimuli. [SEP] Text: fluorescence pulse height; FL vs. FS in log scale and FL vs. SS in log scale. Mean fluorescence values and coefficient of variation (CV value) of the fluorescence of both sample and standard were obtained for at least 1,300 nuclei in each G1 peak, whenever possible. Samples with CV values above 5% were discarded, prepared and ran again. At least three individuals from every population were used to estimate genome size (Table S2), in different days, to account for the variation generated by the flow cytometer. The remaining individuals were analyzed in pool (three or four individuals) to determine ploidy level (Table S2), only. The absolute DNA content of a sample was calculated based on the following formula: 2C nuclear DNA content of the sample = (sample G1 peak mean)/(standard G1 peak mean) × 2C DNA content of standard. Descriptive statistics were calculated for genome size data (mean, standard deviation of the mean, standard error, coefficient of variation and minimum and maximum values) using 2016. Differences in average genome size values among regions were assessed by means of Linear Mixed-with the formulation of Laird & Ware (1982), with a region as fixed factor and population within region as a random nested factor, in R-3. 2. 0 (R Team, 2010). Data was plotted in BoxPlotR (Spitzer et al. , 2014). of fresh leaf tissue sampled from seedlings germinated from wild seeds of individuals from 52 populations from and Australia (Table S1), showed no significant differences in genome size (F5,44 = 0. 58; p = 0. 716) among regions (Fig. 1). All individuals (N = 477) were found to be diploid, presumably with 2n = 16 chromosomes. Average genome size ranged from 1. 70 pg/2C (SD = 0. 06 pg) in Australia and Spain (SD = 0. 06 pg) to 1. 71 pg/2C (SD = 0. 06 pg) in Chile, 1. 72 pg/2C (SD = 0. 06 pg) in Argentina and California (SD = 0. 07 pg) and 1. 73 pg/2C (SD = 0. 07 pg) in Turkey (Table 1). Figure 1: Comparison of genome size among native and non-native genotypes of Centaurea solstitialis. [SEP] Justify:

Output: The text provides evidence about the variability in responses to environmental stimuli through the measurement of genome size across different populations and regions. It notes significant differences and variability, as shown by the coefficient of variation (CV value) and the assumptions drawn from the data analysis, indicating that individuals do not respond uniformly to environmental stimuli. Furthermore, the statement that 'samples with CV values above 5% were discarded' supports the idea that variations in response exist among the individuals analyzed.


Input: Task: pass the claim using the given text. Claim: Phonetics analyzes the sounds of human speech. [SEP] Text: The two words consist of one syllable, and they are frequently connected to adjacent words. In addition, typical pronunciation problems of the Korean participants seemed to be related to the lateral [l] sound and the lax vowel in the word “look”. The lateral must be produced like a Korean flap in casual production of the English word “water”. The lax vowel [ʊ] is also quite difficult for Koreans to realize sufficient vowel quality (Yang & Whalen, 2015). The words “form” and “path” ranked third and fourth. A few instances of the word “form” were wrongly recognized as “from”. Several instances of the word “path” were recognized as “pet, pat, pass, past, pets”. Both the vowel quality and the fricative features could account for the variants. The second to fourth words on the list have either a fricative onset or coda, which must have contributed to the low recognition rate. Yang (2017) reported the same recognition problem in a paragraph with words with fricative codas, such as “slabs” and “these”. He attributed the low recognition rate of casual speech to problems of individual pronunciation errors and Google soundwriter errors with the fricative sounds. Similar fricative problems could be found with the function words on the list. Yang also noted that the main error sources might be traced to the phonotactic probability (Vitevitch & Luce, 2004) and lexical neighborhood density (Luce & Pisoni, 1998) of the words in the paragraph. The vowel in the word “ends” was recognized as “and, ann’s, as, hands,” and others. The quality of the vowel might have to be considered for better recognition. A study of the recognition rate of a separate list of minimal pairs of vowels for the same participants might be useful to explain partial causes of the total recognition rate of a passage, including either one or the other minimal pair of words. A single sound production might not provide a full explanation of the holistic evaluation of the passage, as in Kang & Ahn (2013). These authors attempted to compare the accuracy of the English [r] sound and the intelligibility of the thirty Korean students to find no significant relationship. [SEP] Justify:

Output: The text does not directly support or refute the claim regarding phonetics analyzing the sounds of human speech. Instead, it discusses specific pronunciation issues experienced by Korean participants related to certain English sounds, but does not provide a broader analysis of phonetics as a whole.


Input: Task: corroborate the claim using the given text. Claim: Hydroponics allows for soil-less farming, using nutrient-rich water instead. [SEP] Text: According to Bafdal, Dwiratna & Kendarto (2017), this technology is an advancement over earlier ones. Smart watering is the system’s registered trademark. The valve for the proposed self-aware fertigation is built to adhere to gravity and pressure laws. It implies that the valve will automatically open and shut depending on the predetermined height, enabling adequate nutrient circulation. This kind of technology is excellent for use in places without electricity. A hydroponic intelligent plant care system that uses IoT technology to control the environment was created by Paulchamy et al. (2018). IoT allows users to make changes by quickly adding or removing sensors and actuators. By managing the water sprinkling and pump flow, the IPCH box effectively reduces the CO2 concentration. According to the level, the flow of nutrients to hydroponic plants is automatically increased. The challenging step is maintaining a steady pH level in the water solvent. The crop can be grown anywhere in hydroponics, where the growth rate is 90% more than in regular farming. The novelty of the proposed method for distributing nutrient solution in hydroponic plants lies in its groundbreaking approach to optimizing plant growth through advanced modeling techniques. Unlike existing convolutional neural network (CNN) and deep neural network (DNN) models, this innovative system leverages a unique combination of data-driven insights and real-time feedback mechanisms to achieve unparalleled accuracy. The model’s claim to surpass existing CNN and DNN models is rooted in its ability to adapt and learn dynamically from the intricate interplay of variables affecting plant nutrition. By integrating cutting-edge sensor technologies and machine learning algorithms, the system not only precisely distributes nutrient solutions tailored to the specific needs of each plant but also continuously refines its predictions based on live environmental data. This adaptive and responsive nature sets it apart, positioning it as a pioneering solution in the realm of hydroponic agriculture, promising enhanced crop yields and resource efficiency. Proposed system and system design The ratios of nutrients will keep changing due to plant type, plant stage, plant organ focus, air temperature, and humidity. Automatic hydroponic nutrient management must focus on- Taking complete control of hydroponics that monitor and regulate everything needed for plants, including nutrients, EC, pH, CO2, temperature, and humidity Estimating nutrient ratios for feeding plants. Automating nutrient supply to dispatch nutrients in the right amounts at the right time. [SEP] Justify:

Output: The text corroborates the claim by highlighting that hydroponics enables plant growth without soil and utilizes nutrient solutions. It details how the system manages nutrient distribution and the growing environment, which aligns with the claim's assertion about soil-less farming using nutrient-rich solutions.


Input: Task: contrast the claim using the given text. Claim: Every individual responds the same way to environmental stimuli. [SEP] Text: Skip to Content eLife home page your research Search by keyword or author Reset form my search to 10. 7554/eLife. 46359 Open access Copyright information Version of RecordJuly 22, 2019 Accepted ManuscriptJune 21, 2019 Open annotations (there are currently 0 annotations on this page). 1,667 views 259 downloads 21 6359. Copy to clipboard Download BibTeX Download. RIS Full text Figures and data Peer review Side by side Additional files 10 figures, 1 table and 4 additional files 1 Download asset Open asset Urgent and non-urgent variants of the antisaccade task. (a) The compelled antisaccade task. After a fixation period (150, 250, or 350 ms), the central fixation point disappears (Go), instructing the participant to make an eye movement to the left or to the right (±10°) within 450 ms. The cue is revealed (Cue) after a time gap that varies unpredictably across trials (Gap, 0–350 ms). The correct response is an eye movement (Saccade, white arrow) away from the cue, to the diametrically opposite, or anti, location. (b) The delayed antisaccade task. In this case, the cue is shown before the go signal, during fixation. The interval between cue onset and fixation offset varies across trials (Delay, 100 or 200 ms). In all trials, the reaction time (RT) is measured between the onset of the go signal and the onset of the saccade, whereas the raw processing time (rPT) is measured between cue onset and saccade onset. Figure 2 with 1 supplement Download asset Open asset Perceptual performance in the compelled antisaccade task demonstrates a vortex. Each panel shows a tachometric curve, that is, a plot of the probability of making a correct response as a function of rPT, or cue-viewing time. Colored points are experimental results in overlapping time bins (bin width = 15 ms); light shades indicate ± 1 SE from binomial statistics; black lines are continuous, analytical functions fitted to the data. The vortex is the part of the curve for which saccades are highly likely to be captured and performance drops below chance. It is demarcated by gray shades for individual participants (small panels, P1 – P6) and for the aggregate data set (large panel, All participants). [SEP] Justify:

Output: The text contrasts the claim by describing variations in individuals' responses to stimuli in the context of the compelled antisaccade task. It references different participants (P1 – P6) and their individual performance data, suggesting that responses can differ rather than being the same for every individual.


Input: Task: pass the claim using the given text. Claim: Phonetics analyzes the sounds of human speech. [SEP] Text: In the table, the word “prism” lists fourteen instances of variant forms gathered from both groups. It was frequently recognized as “prison” and other rare forms, such as “present, pleasing, prize”. The nasal consonant coda has low energy; thus, even on the human perception test, it is not very well recognized (Yang, 2005). Yang reported in his perception study that the codas [m, n] were perceived correctly by approximately 35% of the 130 participants, while the onsets [m, n] recorded 83% (see Table 2, Yang, 2005). House (1957) and Ohala (1990) noted that nasals were easily distinguishable from other consonants, but they also were easily confused among nasal sounds. The word “apparently” was recognized as six variant forms like “of parenting, parent Lee, of hair only”. In addition, seven instances of “raindrops” were recognized as “range, ranger, rangers”. A more sophisticated algorithm to sift through possible candidates for recognition might be necessary to provide valid and reliable transcription. Within the function words, the definite 5. List of high ranking content and function words in the frequency counts of unrecognized words by the recognition level and word type Content words Function words High group group group group 14 Is 16 The 24 The 39 Is 12 Looks 15 A 19 A 25 Form 11 Form 14 These 11 Its 17 Ends 10 Path 14 When 8 These 14 Path 10 Arch 12 Its 7 There 12 Man 8 Ends 12 There 7 When 12 Take 7 Take 11 With 5 Above 8 Arch 6 Two 11 Above 4 With 8 According 5 Prism 9 But 4 But 7 People 5 High 8 His 4 Of 6 Prism 5 Legend 8 And 3 And 5 Round 4 People 8 Ever 2 They 5 Shape 4 Shape 8 For 2 At 2 Sunlight 4 End 7 Many 2 Ever 2 Two 4 Man 7 No one 2 His 2 Apparently 3 One 7 They 2 Many 2 Table However, we might have to bear in mind that the results could have been biased by simply having more occurrences of the definite 3. 3. Native raters’ bands Table 6 shows statistics of the IELTS bands by two Canadian raters for the Korean participants’ pronunciation of the rainbow passage. Table 6. Statistics of IELTS band points by two English native raters. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses various recognition studies involving words and their forms, as well as statistics on pronunciation and participant perceptions, without directly addressing phonetics or the analysis of speech sounds.


Input: Task: corroborate the claim using the given text. Claim: Hydroponics allows for soil-less farming, using nutrient-rich water instead. [SEP] Text: Maintain an app that communicates with the farmer and allows remote access to the growing environment. Immediate alerts to the farmer for uncommon incidences in the growing environment. Use a cloud server to maintain day-to-day plant growth status. Block diagram Hydroponics is soilless cultivation that can be grown in any small indoor area. Each requirement must be provided artificially in a controlled environment, whereas everything is naturally available for soil agriculture. The above Fig. 2 depicts the whole idea of our proposed system. Figure 2: Block diagram for proposed automatic nutrient provider for hydroponics farming. Download full-size image DOI: 10. 7717/peerj-cs. 1871/fig-2 Our proposed system aims at developing an auto-dosing system for nutrient management to distribute essential nutrients for plants with less human intervention. The system mainly automates the nutrient supply to prevent under-dosing or overdose. This system calculates and estimates the number of nutrients based on the ratios given at every plant stage or age. The block diagram of the system mainly comprises a growing chamber, water reservoir, NPK mixture pumps, and Arduino microcontroller that connects various sensors to sense different parameters like pH, EC, temperature, and water levels and uses LCD 16 × 2 monitor to display all these parameters. The pH and EC sensors in the system continuously monitor the hydroponic solution. If the recorded pH falls beyond the required range, the system triggers pH adjustment processes, such as introducing pH-up or pH-down solutions, to return the pH to the ideal range. If the EC values exceed the predefined thresholds, the system adjusts the nutrient content by diluting the solution with water or supplementing it with more nutrients. These corrective steps are frequently automated and initiated in real-time to handle any variations as quickly as possible and to guarantee that the nutrient solution remains within the precise parameters conducive to plant health. The system provides a stable and controlled environment by proactively maintaining pH and EC levels, protecting against harmful impacts on nutrient uptake and overall plant development in hydroponic farming. It feels pH and EC in regular intervals and compares recorded values with the minimum threshold already initialized in the system. EC and pH ranges vary from plant to plant. The nutrient solution requirement of the plant is directly dependent on the growth stage of the plant, which causes EC ranges to go for different growth stages. [SEP] Justify:

Output: The text corroborates the claim by explicitly stating that 'Hydroponics is soilless cultivation that can be grown in any small indoor area.' It discusses how hydroponics provides a controlled environment where requirements must be artificially supplied, thereby supporting the idea of soil-less farming utilizing nutrient-rich solutions.


Input: Task: contrast the claim using the given text. Claim: Every individual responds the same way to environmental stimuli. [SEP] Text: Results are from trials (between 1366 and 1534 per participant) in which the high-luminance cue (icon) was shown. Figure 2—figure supplement 1 Download asset Open asset Performance in non-urgent antisaccade trials. All data are pooled across participants and sorted by luminance level, high (bright green), medium (grayish green), and low (dark green). Results are shown separately for easy trials (left side), in which the delay between cue and go onset was 100 or 200 ms, and zero-gap trials (right side), in which cue and go onset were simultaneous. (a) Mean fraction correct in easy trials (± 1 SE, from binomial proportion). (b) Mean RT in easy trials (± 1 SE across trials). (c) Tachometric curves from easy trials. (d) Processing time distributions in easy trials. Both correct and incorrect responses are included. (e–h) As in (a–d) except for zero-gap trials. In easy trials, essentially all rPTs correspond to asymptotic performance. In zero-gap trials, the late rise in the tachometric curve becomes partially observable, but the majority of rPTs still correspond to asymptotic performance. Figure 3 Download asset Open asset Perceptual performance varies as a function of cue luminance. (a) Tachometric curves for trials in which the cue had high, medium, and low luminance (indicated by bright, grayish, and dark green points, respectively). Results are for the pooled data from all participants. The vortex shifts to the right and becomes less deep as luminance decreases. (b) Tachometric curves from three individual participants at each cue luminance level, high, medium and low, as indicated by the icons. Gray shades demarcate the vortex of each curve. In each panel, colored points are experimental results and black lines are continuous fits to the data. Figure 4 with 2 supplements Download asset Open asset Perceptual performance quantified across participants and luminance conditions. Each panel shows one particular quantity derived from the fitted tachometric curves, with results sorted by participant (x axes) and luminance level, high (bright green), medium (grayish green), and low (dark green). Error bars indicate 95% confidence intervals obtained by bootstrapping. [SEP] Justify:

Output: The text contrasts the claim by presenting data that indicates variability in responses across different participants based on cues of varying luminance levels. Specifically, it notes that 'perceptual performance varies as a function of cue luminance,' which implies that individuals do not respond uniformly to environmental stimuli, as their responses depend on individual differences and the stimulus characteristics.


Input: Task: pass the claim using the given text. Claim: Phonetics analyzes the sounds of human speech. [SEP] Text: SD indicates the standard deviation; Max, the highest instance; Min, the lowest instance B Average 6. 0 6. 7 SD 0. 8 0. 9 Max 8. 0 8. 5 Min 5. 0 5. 0 average, both raters assigned 6. 4 band point for the read speech of the participants. Figure 1 illustrates the actual data points of the IELTS bands for the participants. applied more lenient criteria than Rater A, which can be seen from the line of equity. The ranges of the two raters were almost the same by 0. 5 band points. The bands of the participants ranged from 5. 0 to 8. 0. The relationship showed a moderately high correlation with a standard deviation less than band point 1. The absolute difference between the two raters’ bands ranged from 1. 0 to 1. 5 band points. Correlation analysis was conducted between the IELTS band points of the two raters to obtain a correlation coefficient of r=0. 77 (p<. 05). The narrow range without the higher or lower bands might have caused the low coefficient. We could have recruited participants with lower levels of fluency; then, the low recognition would not have produced valid and reliable outputs. However, the correlation might be stronger if the recognition worked appropriately to yield distributed recognition data. An additional correlation analysis was conducted between the number of all of the correctly recognized words and the raters’ bands to obtain a correlation coefficient of r=0. 467 (p<. 05), indicating a significant but very weak correlation. Figure 1. Distribution of the IELTS band points by two raters. A line of equity is drawn through the band points. analysis between the number of correctly recognized content words and the raters’ bands yielded a correlation coefficient of r=0. 567 (p<. 05), while that between the number of correctly recognized function words and the raters’ bands produced a correlation coefficient of r=0. 208 (p>. 05). The raters’ bands seem to depend more on the correct recognition of content words. We can state that the speech recognition application could provide partial assistance for the evaluation of the participants’ fluency level. Since the parts of the passage matter, we might have to use a lexically balanced passage with an appropriate number of content and function words to gain the greatest advantage from the application for evaluation purposes. [SEP] Justify:

Output: The text does not address the claim directly regarding phonetics or its analysis of speech sounds. Instead, it discusses correlation analyses related to IELTS band scores, speech recognition applications, and fluency levels without mentioning phonetics or sound analysis.


Input: Task: corroborate the claim using the given text. Claim: Hydroponics allows for soil-less farming, using nutrient-rich water instead. [SEP] Text: If the observed pH value is outside the predefined range, remedial measures are being taken to restore a workable pH range. As well as it is checking whether the recorded EC value is higher, lower, or feasible. If recorded EC values are higher, switch on the water pump to reduce the nutrient concentration. On the other hand, if ppm goes down, change on NPK mixture pumps to increase the nutrients in the reservoir. algorithm is a sophisticated mechanism that determines the developmental phases of plants in a hydroponic environment, ensuring exact nutrient administration adapted to each growth stage. This program uses multiple data sources to make informed conclusions about the plant’s age. Environmental sensors, such as those that measure temperature, humidity, and light intensity, provide real-time information on growing conditions. Furthermore, nutrient sensors monitor the composition of the hydroponic solution, providing information about the plant’s nutritional requirements. This abundance of data is processed by the algorithm, which then applies programmed growth patterns appropriate to the farmed plant species. These patterns, which range from germination to vegetative growth, blooming, and fruiting, serve as a guide for determining the present stage of growth. Machine learning techniques are used in some implementations to improve the algorithm’s capabilities by learning from prior data and adjusting to changing environmental conditions. The decision-making mechanism of the algorithm causes the dosing system to distribute the correct amount and composition of nutrients based on the recognized growth stage. In hydroponic farming practices, this dynamic and adaptable technique guarantees that plants receive personalized nourishment throughout their lifecycle, optimizing their health and productivity. While supplying nutrients, the system executes the Identification algorithm to identify the age of the plant and provide the correct quantity of nutrients accordingly. NPK pumps continue flowing nutrient solution for the period calculated in Eqs. (1), (2), or (3) according to the plant stage. at Site app connects the autonomous dosing system to the farmer’s mobile smartphone, allowing rapid access to important information. The IoTCloudData cloud server collects and processes data from the hydroponic setup as a centralized hub. The farmer may remotely monitor critical variables such as nutrient levels, pH, and environmental conditions via the app. The system sends data on these parameters to the cloud server in real time, and the View at Site app retrieves it and displays it on the farmer’s mobile device in an easily understandable way. [SEP] Justify:

Output: The text corroborates the claim by detailing the hydroponic farming process, which inherently involves soil-less cultivation. It explains how the system manages nutrient concentrations and provides exact nutrient administration to plants using a liquid solution, highlighting the use of nutrient-rich water rather than soil for plant growth. This aligns directly with the claim regarding hydroponics facilitating soil-less farming.


Input: Task: contrast the claim using the given text. Claim: Every individual responds the same way to environmental stimuli. [SEP] Text: (a) Mean perceptual accuracy, calculated as the average value of the fitted tachometric curve for rPTs between 0 and 250 ms. (b) Vortex time, calculated as the rPT at which the minimum of the fitted tachometric curve is found. (c) Endogenous response centerpoint, equal to the rPT at which the rise of the fitted tachometric curve is halfway between its minimum and maximum values. Figure 4—figure supplement 1 Download asset Open asset Additional quantities that characterize perceptual performance across participants and cue conditions. Each panel shows one particular feature derived from the fitted tachometric curves, with results sorted by participant (x axes) and luminance level, high (bright green), medium (grayish green), and low (dark green). Error bars indicate 95% confidence intervals obtained by bootstrapping. Same format as in Figure 4. (a) Maximum slope attained during the rising phase of the tachometric curve. (b) Vortex depth, equal to the minimum fraction correct. Note that, for participants 1, 4, and 6, the depth is zero for the high-luminance cue. (c) Left edge of the vortex, equal to the rPT at which the dip of the tachometric curve is halfway between chance (0. 5) and its minimum value. Although these metrics are somewhat noisier than those shown in Figure 4, the effects of luminance are again highly consistent across participants, albeit with significant quantitative differences. Figure 4—figure supplement 2 Download asset Open asset Simulated perceptual performance quantified in the same way as the experimental data. Results were obtained with the exact same analyses as those in Figure 4 (Materials and methods), except that they were based on simulated trials. The model data were generated using the best-fitting model parameters for each individual participant. Same format as in Figure 4. Figure 5 with 4 supplements Download asset Open asset Dissociation between perceptual capacity and overall task performance. In each panel, the data from each participant (joined by lines) are shown for trials of high, medium, and low luminance cues (bright, grayish, and dark green points, respectively). Crosses indicate the typical (median) uncertainty (2 SEs) associated with the measurement in each direction. correlations between values on the x and y axes are indicated, along with significance (Materials and methods). The partial correlation eliminates the association due exclusively to luminance. [SEP] Justify:

Output: The text contrasts the claim by highlighting that there are 'significant quantitative differences' in the effects of luminance across participants. This implies that individuals do not respond the same way to the same environmental stimulus, as their perceptual performance metrics differ from one another.


Input: Task: pass the claim using the given text. Claim: Phonetics analyzes the sounds of human speech. [SEP] Text: Were the passage lexically unbalanced, one solution would be to focus more on the recognition of content words, as Loukina et al. (2015) did. In addition, the two raters must have chosen the band point after considering not only the clear and correct pronunciation of each given word but also impressions of prosodic aspects of the passage. Any perfect agreement of the subjective evaluation might not be possible, but modifying mismatching band points among the raters after a round of evaluation might be required to secure the validity and reliability of the final band points. Further studies on the relationship between subjective human evaluation and objective machine recognition with more participants and passages might reveal hidden aspects of the evaluation. 4. Summary and study examined Korean students’ pronunciation of an English passage using a speech recognition application and human raters’ evaluations of their speech according to the band criteria of the IELTS speaking section. Thirty-one graduate and undergraduate students in a phonetics course participated in the recording of the English passage. An application called Speechnotes was employed to collect word recognition rates for the passage. Two experienced Canadian raters evaluated the recorded speech. The results showed that the grand average percentage of correctly recognized words was 77. 7% with a standard deviation of 6. 3%. The moderate recognition rate implied the pronunciation level of participants’ as intermediate and higher. The content word groups showed lower recognition and wider deviation, which might be related to some pronunciation errors of specific consonants or vowels by the participants. The recognition rate varied depending on the composition of the content and function words in each given sentence. Frequency counts of unrecognized words by group level and word type revealed the typical pronunciation problems of the Korean participants. The fricatives and nasals led to low recognition rate along with the syllable positions. Various distributions of unrecognized words were observed among the participants and proficiency groups. The function words and specifically the definite 0. 77. An analysis between the number of correctly recognized content words and the raters’ bands yielded a correlation coefficient of r=0. 567, while that between the number of correctly recognized function words and the raters’ bands produced an almost a negligible correlation. From these results, the author concludes that the speech recognition application could constitute a partial aid to diagnose each individual or group’s pronunciation problems, but further study is still needed to match the human raters in lexically balanced passages or free speech. 1. [SEP] Justify:

Output: The text is irrelevant to the claim about phonetics analyzing human speech sounds. It discusses an evaluation of Korean students’ pronunciation using speech recognition and human raters, but does not directly address the concept of phonetics as a discipline focused on the sounds of speech. Therefore, it does not confirm or contradict the claim.


Input: Task: corroborate the claim using the given text. Claim: Hydroponics allows for soil-less farming, using nutrient-rich water instead. [SEP] Text: The pH meter calibrates the acidity or alkalinity of nutrient explanation in the water tank. In this system, we have grown tomato plants for the experimental results, and tomato plants can grow at a 5. 5 to 6. 5 feasible pH range. At all times, pH should be checked after getting EC in the predetermined range. The pH is too low or too high can stop nutrient uptaking and causes some deficiencies in plants. We should use pH up or down solutions to bring into the correct pH ranges. EC meter: EC meter and pH meter supports feeding hydro plants nutrients at consistent levels. Electrical conductivity (EC) can be measured in millisiemens (mS) or parts per million (ppm). For tomato plants, optimal EC ranges can be from 2 to 5 mS or 1,400 to 3,500 ppm levels based on the type of crops and growth stage of the tomato plants. If the EC value decreases, plants consume soundly and switch ON NPK pumps to raise nutrient solution. If the solution’s EC goes up, it means more nutrients in the resolution, and switching to the ON water pump dilutes the solution. Ultrasonic sensor: An ultrasonic sensor (HC SR04) is used to regulate the water level in the water tank. It is used to degree distance from one object to another object. It controls the water pump to turn on or off, thus avoiding water wastage. If the water equal recorded is less than the inception, it prompts the water pump to turn ON; otherwise, it will turn OFF immediately. 20 × 4 LCD: We used 20 columns × 4 rows of character LCD monitor designed for Arduino microcontroller with 16 pins to display all the input from sensors. 328 ADC: This device used for analog to digital conversion and vice versa. are using deep water culture for growing plants. Submersible pumps are used to mix the nutrient solution into the water reservoir. Hydroponic plants are soilless and consume macro and micro nutrients for their growth. It is essential to remember that the number of hydroponic nutrients and ratios that plants often require increases as plants get grown up. Then they slowly decrease as the plant enters the reproduction or harvesting stage. An auto-dosing system, designed to deliver nutrients mainly to concentrate on the plat stage, should fix specific nutrient ratios accordingly. Let us see how tomato plants consume nutrients at different stages of their growth. [SEP] Justify:

Output: The text corroborates the claim by clearly stating that 'Hydroponic plants are soilless and consume macro and micro nutrients for their growth.' This directly supports the assertion that hydroponics involves soil-less farming and reliance on nutrient-rich water solutions.


Input: Task: contrast the claim using the given text. Claim: Every individual responds the same way to environmental stimuli. [SEP] Text: (a) Mean observed accuracy versus mean perceptual accuracy. (b) Mean observed accuracy versus mean RT. Average RT data include both correct and incorrect trials. (c) Mean perceptual accuracy versus mean RT. Figure 5—figure supplement 1 Download asset Open asset Dissociation between perceptual capacity and overall task performance based on the curve centerpoint. Same format as in Figure 5, except that the endogenous response centerpoint is plotted instead of the mean perceptual accuracy. (a) Mean observed accuracy as a function of the centerpoint. (b) Mean observed accuracy as a function of mean RT. (c) Centerpoint as a function of mean RT. The centerpoint relates to the mean observed accuracy and the mean RT (this figure) in nearly identical ways as the mean perceptual accuracy (Figure 5), if one takes into account that a lower centerpoint corresponds to better perceptual performance. Figure 5—figure supplement 2 Download asset Open asset Decoupling perceptual and motor performance. All results are based on data aggregated across participants. Each panel compares results in fast (F) versus slow (S) blocks of trials, which were sorted as follows. First, the 30 blocks of trials performed by each participant were ranked, post hoc, according to mean RT. Then the 10 blocks at the top and the 10 at the bottom were designated as the fast and slow blocks, respectively. Finally, the fast and slow blocks were separately pooled across participants to yield two corresponding groups of trials. (a) Mean RT (± 1 SE) in compelled antisaccade trials. Bar colors, bright, grayish, and dark green, correspond to cue luminance, high, medium, and low, respectively. (b) Mean observed accuracy, equal to the measured fraction of correct responses (± 1 SE from binomial proportion), in compelled antisaccade trials. Note that, for a given luminance, the observed accuracy was higher in the slow than in the fast blocks. (c) Mean perceptual accuracy, equal to the mean value of the fitted tachometric curve over the 0–250 ms rPT range (± 1 SE from bootstrap). Note that perceptual accuracy was slightly lower in the slow than in the fast blocks. (d) Tachometric curves for fast (cyan dots) and slow blocks (gray dots). Each panel shows data for a specific cue luminance level, as indicated by the icons. Vertical lines mark the centerpoints of the fitted curves. [SEP] Justify:

Output: The text contrasts the claim by presenting data on the variability of responses to environmental stimuli. It discusses how mean observed accuracy and reaction time (RT) differ between fast and slow blocks of trials across participants, indicating that responses are not uniform. Specifically, it notes that 'the observed accuracy was higher in the slow than in the fast blocks', which implies that individuals do not respond the same way to stimuli depending on conditions.


Input: Task: pass the claim using the given text. Claim: Phonetics analyzes the sounds of human speech. [SEP] Text: Benner, M. L. (2020). Parts of speech. Retrieved from 2. House, A. S. (1957). Analog studies of nasal consonants. Journal of Speech and Hearing Disorders, 22(2), 190-204. 3. IDP Education Canada. (2020). IELTS. Test format. Retrieved from 4. Kang, S. , & Ahn, H. (2013). An intelligibility-based approach to English pronunciation teaching: Evidence from [r] production. Language Research, 49(3), 631-646. 5. Levis, J. (2011). Assessing speech intelligibility: Experts listen to two students. In J. Levis, & K. LeVelle (Eds. ), Proceedings of the 2nd Pronunciation in Learning and (6. Levis, J. , & LeVelle, K. (2011). Pronunciation and intelligibility: An overview of the conference. In. J. Levis, & K. LeVelle (Eds. ), Proceedings of the 2nd Pronunciation in Learning and (7. Loukina, A. , Lopez, M. , Evanini, K. , Suendermann-Oeft, D. , Ivanov, A. , & Zechner, K. (2015, September). Pronunciation accuracy and intelligibility of non-native speech. Proceedings of Interspeech 2015 (8. Luce, P. , & Pisoni, D. B. (1998). Recognizing spoken words: The neighborhood activation model. Ear & Hearing, 19(1), 1-36. 9. Miller, N. (2013). Measuring up to speech intelligibility. of Language & Communication Disorders, 48(6), 601-612. 10. Naver. (2020). Papago. Retrieved from 11. Nolan, C. (2012). Fire alarm intelligibility. Paper presented in 2012 CFAA-Technical Seminar. Retrieved from 12. Nordquist, R. (2020). Definition and examples of function words in English. Retrieved from 13. Ohala, J. (1990). The phonetics and phonology aspects of assimilation. In J. Kingston, & M. E. Beckman (Eds. [SEP] Justify:

Output: The text provided lists various references and publications related to speech and hearing, but does not specifically discuss phonetics or analyze the sounds of human speech. Therefore, it is irrelevant to the claim since it does not support, contradict, or relate directly to the analysis of phonetics.


Input: Task: corroborate the claim using the given text. Claim: Hydroponics allows for soil-less farming, using nutrient-rich water instead. [SEP] Text: Tomato plant at germination stage At the time of the seedling or germination stage, the plant supplied nutrients naturally available in the RO water. The seedling can start its growth with lightening, CO2, oxygen, and minimal nutrients. Tomato plant at vegetative stage N-P-K ratios represent the percentage of each nutrient in the solution. For example, the N-P-K ratio 7-9-5 is the best ratio at the vegetative stage that contains 7% of nitrogen, 9% of phosphorous, and 5% of potassium. The remaining solution is filled with varying amounts of micronutrients. During the vegetative stage, plants consume higher amounts of nitrogen in the fertilizer for a rapid growth rate. Nutrient consumption with more nitrogen products makes plants healthier, with leaves seen dark shined greenish. At this stage, plants take around 1,400 to 2,000 ppm of nutrients required for growth. In our system, the minimum threshold of 1,400 ppm and a maximum of 2,000 ppm are taken for nutrient estimation. Tomato plant at reproductive stage (flower/fruit stage) Plants’ reproduction stage starts with flowers that carry out reproductive functions to produce fruits. During this stage, plants consume higher amounts of phosphorous (P) for flower/fruit production and reduce taking nitrogen as it is already collected in vegetative stage at higher levels. Phosphorous is also needed for healthy root structure development. In this stage, potassium is a crucial nutrient for reproduction. In this stage, a 5-15-14 NPK ratio may be a wise choice for plant growth. Plants require around 2,000 to 4,500 ppm of nutrients for optimum growth throughout the blooming or fruiting periods. In our system, the minimum threshold of 2,000 ppm and a maximum threshold of 2,500 ppm has taken. Similarly, for the fruiting stage, the minimum threshold of 2,200 ppm and ultimate point of 3,500 ppm has been accepted for nutrient estimation. Achieving 97. 5% accuracy in recognizing the vegetative stage, 97. 5% in the blooming stage, and 99. 4% in the fruiting stage in hydroponic plants using nutrient solutions has significant implications for precision agriculture. This level of precision enables focused and efficient fertilizer delivery throughout the plant’s growth cycle, optimizing resource efficiency and minimizing waste. [SEP] Justify:

Output: The text corroborates the claim by describing the process and benefits of hydroponic farming, which utilizes nutrient-rich water to provide essential nutrients for plant growth without soil. It details how the nutrient solution is formulated with specific ratios of nitrogen, phosphorous, and potassium, emphasizing the soil-less nature of the hydroponics system.


Input: Task: contrast the claim using the given text. Claim: Every individual responds the same way to environmental stimuli. [SEP] Text: In the high- and low-luminance cases, the blue curve is slightly shifted to the left relative to the gray (asterisks indicate p < 0. 0005 for the difference in centerpoints, from bootstrap). This implies slightly better perceptual performance in the fast than in the slow blocks. Figure 5—figure supplement 3 Download asset Open asset Dissociation between perceptual capacity and overall task performance as seen with the accelerated race-to-threshold model. Results were obtained in the exact same way as those in Figure 5, except that they were based on simulated trials. The model data were generated using the best-fitting model parameters for each individual participant. Same format as in Figure 5. Figure 5—figure supplement 4 Download asset Open asset Model parameters that characterize individual perceptual performance. In each panel, the data from each participant (joined by lines) are shown for trials of high, medium, and low luminance cues (bright, grayish, and dark green points, respectively). Parameter values are as listed in Supplementary file 1. correlations between values on the x and y axes are indicated, along with significance (Materials and methods). The partial correlation eliminates the association due to luminance. (a) Mean perceptual accuracy as a function of the mean afferent delay of the cue (parameter μCUEaff, or mean cue latency). There seems to be a strong, negative association, but it is all due to mutual dependencies on luminance; within each luminance level, cue latency does not predict perceptual accuracy. This is an example of Simpson’s paradox, a statistical effect whereby a trend between two variables disappears or reverses when the data are conditioned on a third variable. (b) Mean perceptual accuracy as a function of the exogenous acceleration (parameter aEX). (c) Mean perceptual accuracy as a function of the endogenous acceleration (parameter aEND). (d) Correlation between endogenous and exogenous acceleration. The negative relationship indicates that participants whose attention is captured strongly by the cue also tend to endogenously shift their visuospatial attention more slowly. Other model parameters showed weaker relationships to perceptual accuracy. Figure 6 Download asset Open asset Three representative single trials of the race-to-threshold model. Traces show motor plans rL toward the left (red) and rR toward the right (black) as functions of time. [SEP] Justify:

Output: The text contrasts the claim by providing analytical data showing that individual participants exhibit different perceptual performances based on luminance conditions. It states, 'within each luminance level, cue latency does not predict perceptual accuracy,' which implies variability in responses among individuals. The mention of Simpson's paradox further indicates that the overall trend does not hold true for every individual, emphasizing that not all respond the same way to stimuli.


Input: Task: pass the claim using the given text. Claim: Language acquisition involves both innate and learned components. [SEP] Text: This integration is ideally carried out as a timely and appropriate reaction to sensory stimuli. While cortical processing is necessary for cognitively demanding tasks, it is not well suited for rapid threat detection and response. However, subcortical processing serves as a neural shortcut that can crudely and rapidly elicit defensive behaviors, bypassing the more deliberate and intricate cortical processing. This efficient processing is partially explained by the fact that subcortical areas are among the earliest brain areas that receive sensory information (Carr, 2015; McFadyen et al. , 2020; Pessoa, 2008; Pessoa and Adolphs, 2010). It is well established that the subcortical circuit from the multisensory thalamus, lateral thalamus (LT) to the basolateral amygdala (BLA) is necessary for the acquisition and the recall of auditory learned threat conditioning in rodents (Barsy et al. , 2020; Edeline and Weinberger, 1992; Iwata et al. , 1986; Lee et al. , 2021; LeDoux et al. , 1984; Romanski and LeDoux, 1992a; Romanski and LeDoux, 1992b; Romanski et al. , 1993; Taylor et al. , 2021). However, the role of the subcortical LT-BLA pathway is underemphasized and understudied in processing innate threats (Kang et al. , 2022). Therefore, we sought to examine this pathway for processing innate threats as well, with the view that a side-by-side comparison may lead to a new mechanistic insight into the similarities and differences between circuits processing innate and learned threats. Here, we show that, as with the learned threat conditioning, the LT-BLA pathway is essential for processing the innately aversive looming stimulus. Inactivation of either the BLA or the BLA-projecting neurons in the LT was sufficient to impair defensive responses to innate and learned threats. Additionally, fiber photometry from the BLA neurons or the LT axons projecting to the BLA showed a rapid rise in their activity to both forms of stimuli. However, the activity was reduced as mice showed habituation to the aversive stimuli. Despite similarities in processing the innate and learned threat, we found that propranolol, a β-adrenergic receptor blocker, specifically impairs the innate defensive response, while the response to the learned threat remains intact. [SEP] Justify:

Output: The text discusses the neural processing involved in responding to innate and learned threats but does not directly address language acquisition or the components involved in it. Therefore, it is irrelevant to the claim, which specifically pertains to how language is acquired.


Input: Task: corroborate the claim using the given text. Claim: Hydroponics allows for soil-less farming, using nutrient-rich water instead. [SEP] Text: With the potential to improve crop health and productivity, such accuracy contributes to the automation of hydroponic systems, decreasing labor requirements and enabling for data-driven decision-making. Furthermore, the environmental benefits, such as reduced nutrient runoff and a smaller ecological imprint, correspond with sustainable farming practices. This high level of precision not only ensures crop consistency, but also presents hydroponic farming as a competitive and environmentally aware strategy in modern agriculture. Equations for nutrients estimation based on the stage Estimating and calculating the ratios of nutrients to add to nutrient solutions is a primary issue in the hydroponic controlled environment. In India, the hydroponics culture is beginning. Most urban people are aware of growing hydroponics. In this urban farming, a farmer is tightly engaged with his day schedules. They cannot be time-intensive in dosing plants and making pH or EC adjustments. And if he is new to farming, he may accidentally shock his plants by over- or under-dosing. Overdosing on nutrients can result in a nutritional burn, the creation of salt content, and even plant death. Underdosing of nutrients sometimes results in plant decreases. The use of automated dosing systems is the solution to this problem. This system is used to avoid human errors and simplify nutrient management with less human intervention (dosing, checking levels, measuring pH and EC). Normally EC is measured in millisiemens. We can convert this EC to ppm using 500 NaCl or 700 KCl scales. 1MS=500ppm=EC500(or)1MS=700ppm=EC×700 For the tomato plant, the optimal EC range is from 2 to 5 mS, i. e. , 1,400 to 3,500 ppm, according to the KCl scale. We already discussed that plant absorbing nutrients involves several factors such as on plant stage, type of plant, and plant part growing. Accordingly, nutrient consumption at the vegetative stage is different from the flower stage, and similarly, nutrient uptaking at the flower stage is different from the fruit stage. At the germination stage, the plant uses a tiny percentage of nutrients as it can grow with nutrients available in fresh RO water. When it has grown in 30–40 days, leaves increase with height, around 20 to 30 cm. This stage is called the early vegetative stage. [SEP] Justify:

Output: The text corroborates the claim by discussing the hydroponic systems that rely on nutrient-rich water for plant growth. It highlights how hydroponics improves crop health and involves accurate nutrient management without the need for soil, thereby reinforcing the basic premises of soil-less farming.


Input: Task: contrast the claim using the given text. Claim: Every individual responds the same way to environmental stimuli. [SEP] Text: Because in these examples the cue is assumed to be on the left, these variables also correspond to motor plans toward the cue (red) and the anti location (black), respectively. After the exogenous response interval (ERI, pink shade), the former (incorrect) plan decelerates and the latter (correct) plan accelerates. A saccade is triggered a short efferent delay after activity reaches threshold (dashed lines). (a) A correct, long-rPT trial; that is, an informed choice (RT = 369 ms, rPT = 219 ms). (b) An incorrect trial with rPT within the vortex; that is, a captured saccade (RT = 283 ms, rPT = 133 ms). (c) A correct, short-rPT trial; that is, a correct guess (RT = 206 ms, rPT = 56 ms). In all examples, the gap is 150 ms. The influence of the cue depends on its timing relative to the ongoing motor activity. Figure 7 Download asset Open asset Contributions of two distinct neural mechanisms to attentional/oculomotor capture. Top row: representative single, long-rPT trials from the model. Second row: tachometric curves, simulated (black traces) and experimental (green dots). Third row: rPT distributions for correct trials (fC), simulated (black traces) and experimental (green shades). Bottom row: rPT distributions for incorrect trials (fI), simulated (black traces) and experimental (red shades). (a) Results from a restricted version of the model in which, during the ERI, the motor plan toward the cue accelerates but the plan toward the anti location keeps advancing, unperturbed. (b) Results from another restricted version of the model in which, during the ERI, the motor plan toward the anti location halts but that toward the cue keeps advancing, unperturbed. (c) Results from the full-blown model, in which, during the ERI, the cue plan accelerates and the anti plan halts. For each model variant, results were obtained with the parameter values that minimized the error between the model and the pooled experimental data in the high luminance condition (Materials and methods). Figure 8 with 3 supplements Download asset Open asset The race-to-threshold model accounts for antisaccade performance. [SEP] Justify:

Output: The text contrasts the claim by discussing the variability in response to environmental cues as illustrated through the examination of motor plans and saccade performance in various trials. The analysis of correct and incorrect trials, as well as the influence of cue timing, supports the notion that responses can differ significantly among individuals, as each trial can lead to different outcomes based on contextual factors. This indicates that responses to environmental stimuli are not uniform across individuals.


Input: Task: pass the claim using the given text. Claim: Language acquisition involves both innate and learned components. [SEP] Text: Results BLA activity is required for processing a visual innately aversive threat and aversive conditioning Threat conditioning is an associative learning paradigm where an initially neutral tone (conditioned stimulus [CS]) is repeatedly paired with an aversive footshock (unconditioned stimulus [US]). The next day, mice, upon exposure to the CS, show freezing responses (conditioned response [CR]), indicating successful learning of the association (Blair et al. , 2001; Pape and Pare, 2010). As for the innately aversive threat, we used the looming stimulus, an overhead expanding black disk that is thought to mimic an approaching aerial predator (Yilmaz and Meister, 2013). Unlike the tone used in threat conditioning, the looming stimulus triggers defensive responses without prior learning. The defensive response may vary from freezing to escapes and tail rattling (Yilmaz and Meister, 2013; Salay et al. , 2018). In this study, we tested mice in an arena devoid of shelter (Shang et al. , 2018). This setup promotes freezing as the dominant defensive response, comparable to the freezing response observed in threat conditioning. Although the mice showed extended freezing beyond the looming stimulus period, we observed rapid habituation to the repeated presentation of the loom (Figure 1—figure supplement 1A–C). Figure 1 with 4 supplements see all Download asset Open asset The basolateral amygdala (BLA) activity is required for processing innate as well as learned aversive signals. (A) Experimental design of the in vivo electrophysiology experiment. Mice were injected unilaterally with AAV vectors expressing ChrimsonR in the lateral thalamus (LT) and with hM4Di or m-Cherry in the BLA. (B) Clozapine-N-oxide (CNO) reduces the amplitude of the field excitatory postsynaptic potential (fEPSP) in hM4Di- but not m-Cherry-expressing neurons. Left panel: fEPSP is unchanged after CNO injection in the m-Cherry group. Middle panel: fEPSP is reduced after CNO injection in the hM4Di group. Shadowed area represents the SEM. Scale bar, 5 ms, 0. 1 mV, the red bar represents the pulse of light (0. 5 ms, 638 nm). [SEP] Justify:

Output: The text discusses the role of the basolateral amygdala in processing innate and learned aversive signals, but it does not address language acquisition specifically. Therefore, it is irrelevant to the claim regarding language acquisition.


Input: Task: corroborate the claim using the given text. Claim: Hydroponics allows for soil-less farming, using nutrient-rich water instead. [SEP] Text: The plant expenses around 1,400 to 2,000 ppm of mixed macro and micronutrients for its happy growth. In this entire stage, the plant consumes more nitrogen with around a 7-9-5 NPK ratio. That means the tomato plant takes 7% of nitrogen, 9% of phosphorous, and 5% of potassium out of the total nutrients provided. Our system continuously measures pH and EC values in a growing environment. If EC measured is less than the minimum threshold at the vegetative stage, then the system immediately switches on NPK pumps for the time Tveg micro seconds. (1) Tveg=CX(−SURppm)FR Here, C is the capacity of the nutrient reservoir. is the maximum limit of nutrients needed for tomato plants at the vegetative stage, SURppm is surplus ppm of nutrients available in the nutrient reservoir. FR is flowing pump rate. Next to the vegetative stage, plants begin reproduction and flowering in 40–65 days, called the flower stage. In this stage, the plant expenses around 2,000 to 4,500 ppm of mixed macro and micronutrients for healthy growth. In this stage, the plant consumes less nitrogen but more phosphorous and potassium with around a 5-15-14 NPK ratio. That means the tomato plant takes 5% of nitrogen, 15% of phosphorous, and 14% of potassium out of the total nutrients provided. When the system finds an EC range below the minimum threshold, it is necessary to switch on NPK pumps for Tflow ms. The same calculation is done at the fruiting stage with a point change. (2) Tflow=CX(−SURppm)FR (3) Tfru=CX(−SURppm)FR Here, C is capacity of nutrient reservoir. is the maximum limit of nutrients needed for tomato plants at the flowering stage, is the maximum limit of nutrients needed for tomato plants at the fruiting stage, SURppm is surplus ppm of nutrients available in the nutrient reservoir. FR is flowing pump rate. The tomato plants start to fruit. It is a very crucial stage, and constant attention is needed. In this Fruit stage, plants’ nutrient consumption equals the flowering stage. When EC recordings are not optimal, then it is required to switch on NPK pumps for the time Tfru. [SEP] Justify:

Output: The text corroborates the claim by detailing the nutrient management in hydroponics, where plants are grown in a system that supplies water rich in macro and micronutrients. The description of nutrient consumption by tomato plants at various growth stages emphasizes the lack of soil, which aligns with the claim of soil-less farming using nutrient-rich water.


Input: Task: contrast the claim using the given text. Claim: Every individual responds the same way to environmental stimuli. [SEP] Text: (a) Tachometric curves for high (left), medium (middle), and low (right) luminance cues. Continuous lines are model results. (b) Processing time distributions for correct (shades) and incorrect trials (red traces) at each luminance level. Overlaid traces (black and dark red) are corresponding model results. (c) RT distributions for correct (shades) and incorrect trials (red traces) at individual gap values (125 and 175 ms) for each luminance level. Overlaid traces (black and dark red) are model results. Dotted vertical lines mark the rPT at which the vortex reaches its minimum point (vortex time). All empirical data are pooled across participants. Figure 8—figure supplement 1 Download asset Open asset The race-to-threshold model reproduces average performance in individual gap conditions. (a) Mean fraction of correct choices as a function of gap. Circles are experimental results for high (bright green), medium (grayish green), and low luminance (dark green) conditions; continuous lines are model results. (b) Mean RT as a function of gap. Same conventions as above. All experimental points represent data pooled across participants. Figure 8—figure supplement 2 Download asset Open asset The accelerated race-to-threshold model individually fitted to the data of participants 1 (top two rows), 2 (middle rows), and 3 (bottom two rows), as indicated on the right. (a) Mean fraction of correct choices (top) and mean RT (bottom) as functions of gap. Circles are experimental results for high (bright green), medium (grayish green), and low luminance (dark green) conditions. Continuous lines are model results. (b–d), Tachometric curves for high (b), medium (c), and low luminance cues (d) are shown in the top panels. Corresponding rPT distributions for correct (shades) and incorrect trials (red traces) are shown in the bottom panels. Black and dark-red continuous lines are model results. For each luminance, the dotted vertical line marks the vortex time. Figure 8—figure supplement 3 Download asset Open asset The accelerated race-to-threshold model individually fitted to the data of participants 4 (top two rows), 5 (middle rows), and 6 (bottom two rows). Same format as in Figure 8—figure supplement 2. [SEP] Justify:

Output: The text contrasts the claim by discussing experimental results and models that demonstrate variability in responses to different luminance conditions among participants. It explicitly states that 'All empirical data are pooled across participants,' indicating that the responses are not uniform but vary by individual.