{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":1058,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":1058,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"9b929e5a7fee","filters":{"topic":"Soil Geostatistics and Mapping"}},"results":[{"id":"W2588003345","doi":"10.1371/journal.pone.0169748","title":"SoilGrids250m: Global gridded soil information based on machine learning","year":2017,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":4665,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Random forest; Landform; Soil texture; Gradient boosting; Soil science; Environmental science; Soil map; Shuttle Radar Topography Mission; Ensemble learning; Spatial variability; Standard deviation; Land cover; Computer science; Remote sensing; Artificial intelligence; Cartography; Mathematics; Land use; Digital elevation model; Statistics; Geology; Soil water","authors":[{"name":"Tomislav Hengl","is_ca":false},{"name":"Jorge Mendes de Jesus","is_ca":false},{"name":"G.B.M. Heuvelink","is_ca":false},{"name":"M. Ruiperez González","is_ca":false},{"name":"Milan Kilibarda","is_ca":false},{"name":"Aleksandar Blagotić","is_ca":false},{"name":"Wei Shangguan","is_ca":false},{"name":"Marvin N. Wright","is_ca":false},{"name":"Xiaoyuan Geng","is_ca":true},{"name":"Bernhard Bauer-Marschallinger","is_ca":false},{"name":"Mário Guevara","is_ca":false},{"name":"Rodrigo Vargas","is_ca":false},{"name":"R.A. MacMillan","is_ca":false},{"name":"N.H. Batjes","is_ca":false},{"name":"J.G.B. Leenaars","is_ca":false},{"name":"Eloi Ribeiro","is_ca":false},{"name":"Ichsani Wheeler","is_ca":false},{"name":"S. Mantel","is_ca":false},{"name":"Bas Kempen","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0233373345359952,"gpt":0.2142657807513585,"spread":0.1909284462153633,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001588924,0.00009566994,0.0001047241,0.00001463369,0.0004750256,0.0001436562,0.0002233074,0.00004029271,0.0005636012],"category_scores_gemma":[0.0003993014,0.00009205398,0.00002384052,0.00004037414,0.00007049833,0.0003092033,0.0001292713,0.0001268079,0.001540198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009886411,"about_ca_system_score_gemma":0.000009375931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008652111,"about_ca_topic_score_gemma":0.000145275,"domain_scores_codex":[0.9991333,0.00001969107,0.0001318913,0.0001262987,0.0003930331,0.0001957529],"domain_scores_gemma":[0.9994409,0.00002718718,0.0001443344,0.0002980602,0.00001045166,0.0000790482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001458309,0.0009823563,0.8938269,0.0001048075,0.00007653712,0.00001622392,0.000341066,0.02315607,0.002575203,0.00122038,0.002468732,0.07508592],"study_design_scores_gemma":[0.0009334729,0.0001787657,0.4615637,0.00009047279,0.00004153664,6.61388e-7,0.00002182229,0.5315074,0.001717171,0.0007078489,0.002973778,0.0002633703],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8288811,0.000005291205,0.001645819,0.0009781349,0.0001008426,0.0001858278,0.00005421721,0.00009797581,0.1680507],"genre_scores_gemma":[0.996968,0.000008550516,0.002200249,0.0004543885,0.00003829921,0.00001076471,0.00005040142,0.000005307131,0.0002640857],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5083514,"threshold_uncertainty_score":0.9992372,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2130560194","doi":"10.1371/journal.pone.0105992","title":"SoilGrids1km — Global Soil Information Based on Automated Mapping","year":2014,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":1297,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Joint Research Centre; Agriculture and Agri-Food Canada; Comisión Nacional para el Conocimiento y Uso de la Biodiversidad, Gobierno de México; Chinese Academy of Sciences; European Commission; Bill and Melinda Gates Foundation; Institute of Soil Science, Chinese Academy of Sciences; Alliance for a Green Revolution in Africa; U.S. Department of Agriculture","keywords":"Soil map; Digital soil mapping; Soil carbon; USDA soil taxonomy; Environmental science; Pedotransfer function; Soil science; Soil survey; Soil water; Soil organic matter; Cation-exchange capacity; Silt; Soil classification; Soil test; Geology","authors":[{"name":"Tomislav Hengl","is_ca":false},{"name":"Jorge Mendes de Jesus","is_ca":false},{"name":"R.A. MacMillan","is_ca":false},{"name":"N.H. Batjes","is_ca":false},{"name":"G.B.M. Heuvelink","is_ca":false},{"name":"Eloi Ribeiro","is_ca":false},{"name":"Alessandro Samuel‐Rosa","is_ca":false},{"name":"Bas Kempen","is_ca":false},{"name":"J.G.B. Leenaars","is_ca":false},{"name":"Markus Walsh","is_ca":false},{"name":"M. Ruiperez González","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01615228860210913,"gpt":0.1963834306529935,"spread":0.1802311420508844,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001775304,0.00009268183,0.000102719,0.00002400235,0.0001025501,0.00004847609,0.0001149964,0.00004409354,0.0003315847],"category_scores_gemma":[0.0001797192,0.00009175971,0.00001975443,0.0001777944,0.0000397198,0.0001679573,0.00005648053,0.00006132675,0.002282389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001264976,"about_ca_system_score_gemma":0.000008263162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001986461,"about_ca_topic_score_gemma":0.00002651807,"domain_scores_codex":[0.9990928,0.00002843736,0.0001627457,0.0001224914,0.0003872583,0.0002062854],"domain_scores_gemma":[0.999612,0.00004523552,0.00007204501,0.0001821711,0.0000110789,0.00007742793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002134512,0.004717326,0.4710634,0.000765448,0.0002956547,0.00001583623,0.00176684,0.1880737,0.02229105,0.01181032,0.06504468,0.2339423],"study_design_scores_gemma":[0.0003340777,0.00006468692,0.1236456,0.00006349094,0.00001293165,2.751499e-7,0.00001590588,0.8725018,0.0006357626,0.0004570635,0.002131781,0.0001365683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7999359,0.000001846592,0.01411414,0.000676692,0.00009265994,0.0002230061,0.00003385622,0.0005897616,0.1843322],"genre_scores_gemma":[0.9910436,0.000001407423,0.007246875,0.00155694,0.00003030517,0.00001383807,0.00004683595,0.000005004661,0.00005522751],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6844281,"threshold_uncertainty_score":0.9984944,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2170874734","doi":"10.1111/1477-8947.12054","title":"Economics of salt‐induced land degradation and restoration","year":2014,"lang":"en","type":"article","venue":"Natural Resources Forum","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":1273,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"United Nations University Institute for Water, Environment, and Health","funders":"","keywords":"Land degradation; Sustainable land management; Land management; Food security; Natural resource economics; Business; Land use; Environmental degradation; Subsidy; Environmental planning; Environmental science; Agriculture; Economics; Geography","authors":[{"name":"Muhammad Farhan Qadir","is_ca":true},{"name":"Emmanuelle Quillérou","is_ca":true},{"name":"Vinay Nangia","is_ca":false},{"name":"Ghulam Murtaza","is_ca":false},{"name":"Murari Singh","is_ca":false},{"name":"Richard J. Thomas","is_ca":false},{"name":"Pay Drechsel","is_ca":false},{"name":"Andrew Noble","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.008226924828737044,"gpt":0.21161795915296,"spread":0.203391034324223,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001175589,0.00004792993,0.00006333837,0.00001891557,0.00005870306,0.00001635629,0.00005130509,0.00003312863,0.00001840589],"category_scores_gemma":[0.0000844625,0.00004178318,0.0000111302,0.00004088067,0.00003727351,0.00008099384,0.00005399869,0.00005051027,0.000009674754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002311351,"about_ca_system_score_gemma":0.000001675253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004012756,"about_ca_topic_score_gemma":0.000712441,"domain_scores_codex":[0.9996299,0.0000165122,0.00009929724,0.0000908557,0.00006797787,0.00009541889],"domain_scores_gemma":[0.999765,0.00005375142,0.00007204946,0.00007481359,0.00000469539,0.00002969313],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007016158,0.000022702,0.4882085,0.00002328658,0.00001312153,3.87737e-7,0.001024182,0.0006258702,0.02175169,0.005713335,0.002051171,0.4804956],"study_design_scores_gemma":[0.0006912895,0.0002088296,0.8306877,0.00002219709,0.000016868,0.000005534646,0.0002844422,0.04948827,0.005056292,0.007934315,0.1053407,0.0002635379],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969262,0.00003337028,0.0001849377,0.0002961589,0.00007505814,0.00005128443,0.000002387748,0.000008406362,0.002422143],"genre_scores_gemma":[0.9990294,0.00001230217,0.0006372829,0.00009966541,0.00001880974,0.000001249406,0.000009443014,0.000003971536,0.0001878794],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4802321,"threshold_uncertainty_score":0.1703869,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2024115582","doi":"10.1119/1.1632486","title":"Unified equations for the slope, intercept, and standard errors of the best straight line","year":2004,"lang":"en","type":"article","venue":"American Journal of Physics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":1255,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Line (geometry); Least-squares function approximation; Unification; Standard error; Point (geometry); Set (abstract data type); Non-sampling error; Applied mathematics; Physics; Observational error; Systematic error; Mathematics; Mathematical analysis; Statistics; Geometry; Computer science","authors":[{"name":"Derek York","is_ca":true},{"name":"N. M. Evensen","is_ca":true},{"name":"Margarita López‐Martínez","is_ca":false},{"name":"Jonás D. De Basabe","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01791943171775219,"gpt":0.2651140590045571,"spread":0.2471946272868049,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001319039,0.00005042927,0.0001038988,0.000006584701,0.00008903651,0.0000108135,0.0001534293,0.000005790837,0.00001930258],"category_scores_gemma":[0.0000598922,0.00002767576,0.00004819098,0.0001463484,0.00045263,0.00004965457,0.0000463122,0.00008039082,0.000001366052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003136325,"about_ca_system_score_gemma":0.00003130648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001094604,"about_ca_topic_score_gemma":0.0000494636,"domain_scores_codex":[0.9995405,0.00001544077,0.0001619343,0.00004801559,0.0001560161,0.00007805805],"domain_scores_gemma":[0.9994143,0.0001450876,0.0002866581,0.00009008485,0.00003265042,0.00003120867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001167904,0.0001804425,0.002919342,0.00001340913,0.0001873247,0.000002050931,0.006331978,0.09310974,0.009118529,0.02164819,0.0006685472,0.8657036],"study_design_scores_gemma":[0.01503711,0.02250153,0.2300494,0.001467337,0.003510091,0.0001506742,0.09901165,0.02536033,0.05373684,0.4493266,0.09753493,0.002313497],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4482196,0.00005511076,0.5487652,0.00203536,0.0001872734,0.0001722625,0.00006744073,0.000002221022,0.000495604],"genre_scores_gemma":[0.9947129,0.00004050069,0.005035002,0.0001204401,0.0000576148,0.000001158458,5.465082e-7,0.000005046234,0.00002677779],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8633901,"threshold_uncertainty_score":0.1667734,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2292439029","doi":"10.1016/j.earscirev.2016.01.012","title":"A global spectral library to characterize the world's soil","year":2016,"lang":"en","type":"article","venue":"Earth-Science Reviews","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":855,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Northern British Columbia; McGill University","funders":"","keywords":"Environmental science","authors":[{"name":"Raphael A. Viscarra Rossel","is_ca":false},{"name":"Thorsten Behrens","is_ca":false},{"name":"Eyal Ben‐Dor","is_ca":false},{"name":"David J. Brown","is_ca":false},{"name":"José Alexandre Melo Demattê","is_ca":false},{"name":"Keith Shepherd","is_ca":false},{"name":"Bo Stenberg","is_ca":false},{"name":"Antoine Stevens","is_ca":false},{"name":"Viacheslav I. Adamchuk","is_ca":true},{"name":"Hamouda Aïchi","is_ca":false},{"name":"Bernard Barthès","is_ca":false},{"name":"Harm Bartholomeus","is_ca":false},{"name":"A. Bayer","is_ca":false},{"name":"Martial Bernoux","is_ca":false},{"name":"Kristin Böttcher","is_ca":false},{"name":"Lukáš Brodský","is_ca":false},{"name":"Changwen Du","is_ca":false},{"name":"Adrian Chappell","is_ca":false},{"name":"Youssef Fouad","is_ca":false},{"name":"Valérie Genot","is_ca":false},{"name":"Cécile Gomez","is_ca":false},{"name":"Sabine Grunwald","is_ca":false},{"name":"Andreas Gubler","is_ca":false},{"name":"C. Guerrero","is_ca":false},{"name":"C. Hedley","is_ca":false},{"name":"Maria Knadel","is_ca":false},{"name":"Héctor José María Morrás","is_ca":false},{"name":"Marco Nocita","is_ca":false},{"name":"Leonardo Ramírez-López","is_ca":false},{"name":"Pierre Roudier","is_ca":false},{"name":"Paul Sanborn","is_ca":true},{"name":"Vincenzo Michele Sellitto","is_ca":false},{"name":"Kenneth A. Sudduth","is_ca":false},{"name":"Barry G. Rawlins","is_ca":false},{"name":"Christian Walter","is_ca":false},{"name":"Leigh Winowiecki","is_ca":false},{"name":"S. Young Hong","is_ca":false},{"name":"Wenjun Ji","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0205138305860025,"gpt":0.2515989711280335,"spread":0.231085140542031,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007635695,0.0001387908,0.000174832,0.00002922125,0.0002606635,0.0001359667,0.0007608455,0.00001434957,0.003750781],"category_scores_gemma":[0.0002334414,0.00006707026,0.00006059333,0.001575504,0.0004884506,0.0005545847,0.000452627,0.0000496665,0.006415648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006249535,"about_ca_system_score_gemma":0.00004661283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004324054,"about_ca_topic_score_gemma":0.0002504652,"domain_scores_codex":[0.9983924,0.00006278739,0.0002569993,0.0004141737,0.0003712691,0.0005023751],"domain_scores_gemma":[0.9991298,0.00004923356,0.00009038104,0.0004766934,0.000005386844,0.0002485606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007112174,0.00003233109,0.01256478,0.000007991038,0.000002126895,0.000009977874,0.0001656669,0.000006209521,0.1460307,0.005267674,0.04059945,0.795306],"study_design_scores_gemma":[0.00005441491,0.00002534791,0.1857103,0.00006210224,0.000003110363,0.000008304318,0.000004141436,0.00001144367,0.002391935,0.0004724381,0.8111315,0.0001249384],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3395874,0.002110711,0.05409672,0.05803974,0.002985899,0.003954229,0.000190968,0.0003895448,0.5386448],"genre_scores_gemma":[0.678539,0.009190942,0.1537961,0.04008692,0.001587725,0.0004946691,0.00001029589,0.00009321275,0.1162012],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.795181,"threshold_uncertainty_score":0.9971599,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2126532874","doi":"10.1034/j.1600-0587.2002.250510.x","title":"A balanced view of scale in spatial statistical analysis","year":2002,"lang":"en","type":"article","venue":"Ecography","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":705,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto; Polytechnique Montréal; University of Alberta","funders":"","keywords":"Scale (ratio); Statistics; Spatial analysis; Range (aeronautics); Autocorrelation; Spatial ecology; Ecology; Temporal scales; Variance (accounting); Variogram; Sample size determination; Sampling (signal processing); Population; Geography; Mathematics; Computer science; Cartography; Kriging; Engineering","authors":[{"name":"Jennifer Dungan","is_ca":false},{"name":"J. N. Perry","is_ca":false},{"name":"Mark R. T. Dale","is_ca":true},{"name":"Pierre Legendre","is_ca":true},{"name":"S. Citron‐Pousty","is_ca":false},{"name":"Marie‐Josée Fortin","is_ca":true},{"name":"A. Jakomulska","is_ca":false},{"name":"Maria N. Miriti","is_ca":false},{"name":"Michael S. Rosenberg","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.007611264277835186,"gpt":0.2122003492496362,"spread":0.204589084971801,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009001089,0.00005942898,0.000156396,0.0001178658,0.00001946724,0.000006424324,0.00008058879,0.00002212699,0.006274213],"category_scores_gemma":[0.00001598738,0.00005760922,0.00006232339,0.0009672065,0.0000995345,0.00002767273,0.00003741945,0.00004538158,0.00008644971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000103445,"about_ca_system_score_gemma":7.591674e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001254425,"about_ca_topic_score_gemma":0.002413457,"domain_scores_codex":[0.9993473,0.000026121,0.0001766067,0.0001593792,0.0001426464,0.0001479931],"domain_scores_gemma":[0.999738,0.00004442821,0.00004251329,0.0001237109,0.000003142008,0.00004818026],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002333645,0.00007056997,0.9532944,0.000005881517,0.00002105457,0.000003136859,0.0001696413,0.0002782372,0.000097818,0.00006968935,0.0006275146,0.04535975],"study_design_scores_gemma":[0.0001484735,0.00002490892,0.9805901,0.000004305117,0.00004276558,2.605962e-7,0.00001653008,0.01700304,0.00003046735,0.0006654621,0.001400915,0.00007275147],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9323389,0.00009980225,0.04405759,0.00006744164,0.0000612623,0.0001197039,0.00009021966,0.00001584238,0.02314925],"genre_scores_gemma":[0.9942108,0.00005218363,0.005631994,0.00005259197,0.000005880986,0.000006375834,0.000008798375,0.000003330476,0.00002804877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06187191,"threshold_uncertainty_score":0.9946342,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2186294614","doi":"10.1016/j.geoderma.2015.11.014","title":"An overview and comparison of machine-learning techniques for classification purposes in digital soil mapping","year":2015,"lang":"en","type":"article","venue":"Geoderma","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":523,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Ministry of Forests; University of Ottawa; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Digital soil mapping; Random forest; Support vector machine; Computer science; Machine learning; Artificial intelligence; Soil survey; Multinomial logistic regression; Sampling (signal processing); Terrain; Soil map; Data mining; Cartography; Soil water; Environmental science; Geography; Soil science","authors":[{"name":"Brandon Heung","is_ca":true},{"name":"Hung Chak Ho","is_ca":true},{"name":"Jin Zhang","is_ca":true},{"name":"Anders Knudby","is_ca":true},{"name":"Chuck Bulmer","is_ca":true},{"name":"Margaret Schmidt","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08048734384441109,"gpt":0.3208146176124165,"spread":0.2403272737680054,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000178071,0.00006406599,0.0001176098,0.00003289119,0.00003663074,0.00003418246,0.00007145928,0.000032693,0.000008298867],"category_scores_gemma":[0.00007498546,0.00006348686,0.00001209269,0.00007922615,0.00005310832,0.0002033779,0.00005535862,0.0000546163,0.000003521523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003105756,"about_ca_system_score_gemma":0.00000620058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002814141,"about_ca_topic_score_gemma":0.0001470733,"domain_scores_codex":[0.9994442,0.0000156464,0.0001753558,0.0001446928,0.000102825,0.0001172114],"domain_scores_gemma":[0.9997267,0.0000395941,0.00008458723,0.00008486691,0.00001158095,0.00005271246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001174992,0.00007517129,0.8212822,0.00004634063,0.000002886744,6.61504e-7,0.001532399,0.0005737872,0.004552792,0.0005194626,0.000221994,0.1711806],"study_design_scores_gemma":[0.0005363025,0.0002268742,0.3421766,0.0000832135,0.000009201171,0.00000593701,0.002370797,0.6204393,0.002689731,0.006465198,0.02472346,0.0002734622],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.975893,0.0004647538,0.02083171,0.0001068479,0.0000287079,0.0002881336,0.00002380409,0.00004689831,0.002316113],"genre_scores_gemma":[0.9946733,0.00002982181,0.005154165,0.00002910239,0.00000933633,0.00002170271,0.00004305313,0.000006712961,0.00003284539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6198655,"threshold_uncertainty_score":0.2588919,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2963253923","doi":"10.1002/wics.1443","title":"Spatial modeling with R‐INLA: A review","year":2018,"lang":"en","type":"review","venue":"Wiley Interdisciplinary Reviews Computational Statistics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":410,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Inference; Code (set theory); Gaussian; Bayesian inference; Bayesian probability; Random field; Algorithm; Theoretical computer science; Mathematics; Artificial intelligence; Statistics","authors":[{"name":"Haakon Bakka","is_ca":false},{"name":"Håvard Rue","is_ca":false},{"name":"Geir‐Arne Fuglstad","is_ca":false},{"name":"Andrea Riebler","is_ca":false},{"name":"David Bolin","is_ca":false},{"name":"Janine Illian","is_ca":false},{"name":"Elias Teixeira Krainski","is_ca":false},{"name":"Daniel Simpson","is_ca":true},{"name":"Finn Lindgren","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05299260366295971,"gpt":0.346729488693779,"spread":0.2937368850308192,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007940757,0.0009537903,0.002755923,0.0001048119,0.000431412,0.00009792398,0.0007577608,0.0001714603,0.002327765],"category_scores_gemma":[0.000164483,0.0006933707,0.000407364,0.0005850505,0.0003591781,0.0001456344,0.001521373,0.0005581361,0.00490017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004475441,"about_ca_system_score_gemma":0.0001734907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007130361,"about_ca_topic_score_gemma":0.0001362531,"domain_scores_codex":[0.9950935,0.0004220287,0.001995032,0.001114837,0.0007988308,0.0005757512],"domain_scores_gemma":[0.9973828,0.000419565,0.00116576,0.0006399528,0.0001051892,0.0002867506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006340798,0.0000676593,0.00000381429,0.02784004,0.00009228869,0.0000606932,0.00004989972,0.0009176409,3.00182e-9,0.0002681725,0.1447557,0.8259377],"study_design_scores_gemma":[0.0001189568,0.0002143853,0.000002078337,0.1166148,0.001066506,0.0002406054,0.000004254219,0.04189641,1.583973e-9,0.002979752,0.8360888,0.000773426],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[5.643641e-8,0.570216,0.4263841,0.00003067179,0.0002142926,0.001363058,0.0006046395,0.00003627618,0.001150924],"genre_scores_gemma":[7.767147e-7,0.888755,0.1071039,0.0002935374,0.0002887909,0.0004076039,0.002759358,0.0001117685,0.0002792377],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8251643,"threshold_uncertainty_score":0.9995518,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W92141931","doi":"10.1016/b978-0-12-800137-0.00003-0","title":"GlobalSoilMap","year":2014,"lang":"en","type":"book-chapter","venue":"Advances in agronomy","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":376,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba; Agriculture and Agri-Food Canada","funders":"","keywords":"Soil map; Computer science; Grid; Terrain; Environmental science; Remote sensing; Soil water; Soil science; Cartography; Geography","authors":[{"name":"Dominique Arrouays","is_ca":false},{"name":"Alfred E. Hartemink","is_ca":false},{"name":"Jonathan Hempel","is_ca":false},{"name":"G.B.M. Heuvelink","is_ca":false},{"name":"S. Young Hong","is_ca":false},{"name":"Philippe Lagacherie","is_ca":false},{"name":"Glenn Lelyk","is_ca":true},{"name":"Alex B. McBratney","is_ca":false},{"name":"N. J. McKenzie","is_ca":false},{"name":"Maria de Lourdes Mendonça-Santos","is_ca":false},{"name":"Budiman Minasny","is_ca":false},{"name":"Luca Montanarella","is_ca":false},{"name":"Inakwu Odeh","is_ca":false},{"name":"Pedro A. Sánchez","is_ca":false},{"name":"James A. Thompson","is_ca":false},{"name":"Gan‐Lin Zhang","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.006945408383292206,"gpt":0.2236333974331402,"spread":0.216687989049848,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001052605,0.000210915,0.0002296396,0.00003073773,0.00004379901,0.00001547106,0.0002327543,0.0001060142,0.004381457],"category_scores_gemma":[0.00001298086,0.0002126607,0.00004992677,0.00002116381,0.0001915595,0.000107355,0.0001875976,0.0001662338,0.002813061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001781913,"about_ca_system_score_gemma":0.000007467987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005696976,"about_ca_topic_score_gemma":0.0003667706,"domain_scores_codex":[0.9989971,0.000007075899,0.0002319058,0.0003716465,0.0001685123,0.0002237837],"domain_scores_gemma":[0.9994744,0.00006402216,0.0001310455,0.0002636726,0.000003503662,0.00006335468],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006173573,0.00000837053,0.004122022,0.00002845004,0.00000731168,0.00002227403,0.00004368678,0.001625019,0.000001449109,0.3436186,0.01161747,0.6388992],"study_design_scores_gemma":[0.000105227,0.00001415598,0.0008256821,0.0000662883,0.000006055805,0.000001683123,0.0000030003,0.00004802951,0.000001262855,0.1115295,0.8871632,0.0002359101],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00003160675,0.001444191,0.003307635,0.0000378485,0.0002492346,0.0001360914,0.000008236281,0.00002305981,0.9947621],"genre_scores_gemma":[0.0120073,0.00226986,0.009879636,0.0005306705,0.000183158,0.00002906727,0.00005465363,0.0000523648,0.9749933],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8755458,"threshold_uncertainty_score":0.9979634,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2070142384","doi":"10.1016/j.cageo.2003.09.006","title":"AgeDisplay: an EXCEL workbook to evaluate and display univariate geochronological data using binned frequency histograms and probability density distributions","year":2003,"lang":"en","type":"article","venue":"Computers & Geosciences","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":360,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Australian Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Histogram; Frequency distribution; Univariate; Kernel density estimation; Probability distribution; Statistics; Computer science; Probability density function; Joint probability distribution; Skew normal distribution; Algorithm; Mathematics; Skewness; Multivariate statistics; Artificial intelligence; Estimator","authors":[{"name":"Keith Sircombe","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05768150800346178,"gpt":0.2877659379496448,"spread":0.2300844299461831,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001100544,0.0001766179,0.0001834729,0.00003456452,0.0007534314,0.0001932575,0.0004772156,0.0000547483,0.00004459777],"category_scores_gemma":[0.0002552136,0.0001478634,0.00001514174,0.0003671535,0.001035306,0.0004407224,0.0007932176,0.000112439,0.000008281641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001258106,"about_ca_system_score_gemma":0.00004596929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002259405,"about_ca_topic_score_gemma":0.0007895246,"domain_scores_codex":[0.9980112,0.0001667421,0.0002194977,0.000904009,0.000279137,0.000419435],"domain_scores_gemma":[0.9989281,0.0001145836,0.0000805509,0.0005370255,0.00001804963,0.0003216486],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004604955,0.0008319938,0.7486656,0.00006435797,0.00004510189,0.0001124056,0.002668928,0.004063992,0.01638151,0.05810487,0.0008440398,0.1681711],"study_design_scores_gemma":[0.0003024028,0.0002279956,0.7757014,0.00003480432,0.00004298825,0.0000585523,0.0001031563,0.1935665,0.0000292198,0.02761134,0.001885497,0.0004361608],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7593985,0.00004498153,0.2397064,0.0001328367,0.0002217066,0.0002398754,0.00004093986,0.00003105463,0.0001836587],"genre_scores_gemma":[0.8585596,0.0000109196,0.1412351,0.0001236435,0.00001516805,0.000004764383,0.00003388321,0.000004144087,0.00001271756],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1895025,"threshold_uncertainty_score":0.6029696,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2111872234","doi":"10.1034/j.1600-0587.2002.250506.x","title":"Conceptual and mathematical relationships among methods for spatial analysis","year":2002,"lang":"en","type":"article","venue":"Ecography","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":356,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal; University of Toronto; University of Alberta","funders":"","keywords":"Ecology; Range (aeronautics); Natural (archaeology); Computer science; Overdispersion; Spatial ecology; Tree (set theory); Spatial relation; Geography; Mathematics; Statistics; Artificial intelligence; Biology; Archaeology","authors":[{"name":"Mark R. T. Dale","is_ca":true},{"name":"Philip M. Dixon","is_ca":false},{"name":"Marie‐Josée Fortin","is_ca":true},{"name":"Pierre Legendre","is_ca":true},{"name":"Donald E. Myers","is_ca":false},{"name":"Michael S. Rosenberg","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04620229349769667,"gpt":0.2868634542855382,"spread":0.2406611607878416,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003099806,0.000064988,0.0001165066,0.00007529066,0.0001461548,0.00002386767,0.00005110129,0.00003851671,0.001812836],"category_scores_gemma":[0.0001362504,0.00006029629,0.00008721732,0.0003690171,0.0002499664,0.00005546142,0.00003496811,0.00005770207,0.00003050259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000064313,"about_ca_system_score_gemma":4.039106e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006679259,"about_ca_topic_score_gemma":0.0001077556,"domain_scores_codex":[0.9994364,0.00005934113,0.0001317118,0.0001730653,0.00006820055,0.0001313249],"domain_scores_gemma":[0.9993751,0.0003978861,0.00004337668,0.0001054684,0.000004466197,0.00007372662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003821663,0.00006932133,0.9204533,0.000007681642,0.0002554333,0.000001139137,0.002463327,0.000265091,0.00007982512,0.0131177,0.002720933,0.06056245],"study_design_scores_gemma":[0.0002177859,0.00003700722,0.8127828,0.000002763398,0.0003096606,8.566467e-7,0.00024009,0.1546424,0.00002471468,0.02554068,0.006044523,0.000156767],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1952993,0.00005027635,0.7956625,0.00006938331,0.00003336883,0.0001525859,0.00001205881,0.00002358488,0.008696984],"genre_scores_gemma":[0.8011131,0.000008249132,0.1986509,0.00003153326,0.00001362293,0.00002537657,0.000006071195,0.000004711181,0.0001464923],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6058137,"threshold_uncertainty_score":0.9990997,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3036873236","doi":"10.1016/j.scitotenv.2020.140338","title":"Machine learning for predicting greenhouse gas emissions from agricultural soils","year":2020,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":283,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Agriculture and Agri-Food Canada","keywords":"Greenhouse gas; Soil water; Agriculture; Environmental science; Natural resource economics; Earth science; Soil science; Economics; Geology; Geography; Archaeology; Oceanography","authors":[{"name":"Abderrachid Hamrani","is_ca":true},{"name":"Abdolhamid Akbarzadeh","is_ca":true},{"name":"Chandra A. Madramootoo","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01326013409874458,"gpt":0.2036675925635267,"spread":0.1904074584647821,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003331564,0.0001186426,0.0001098686,0.000006650311,0.000727363,0.00003132232,0.0006930884,0.00002144872,0.0003385092],"category_scores_gemma":[0.0002426136,0.0000606859,0.00007892864,0.0001841775,0.000780453,0.0001168318,0.0009001051,0.0001542842,0.00005363156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008370949,"about_ca_system_score_gemma":0.00001081249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004265135,"about_ca_topic_score_gemma":0.00000291963,"domain_scores_codex":[0.9986355,0.00003940776,0.0001940779,0.0003019682,0.0005431352,0.0002859437],"domain_scores_gemma":[0.9993417,0.0001178778,0.0001601395,0.0002455786,0.000002996609,0.0001317505],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002177698,0.00005447683,0.002213987,0.000005222892,0.00001568843,4.939382e-7,0.003587921,0.5551241,0.4318709,0.0001309276,0.0004364263,0.006538095],"study_design_scores_gemma":[0.000759321,0.0003471694,0.2657621,0.00004869112,0.00009721277,0.000008785403,0.001955491,0.6758393,0.05022958,0.002057875,0.002473254,0.0004212739],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938836,0.00004350457,0.0007131099,0.003543484,0.0001039057,0.0003335646,0.00003624966,0.00002184809,0.001320778],"genre_scores_gemma":[0.9980518,0.00002552995,0.001353545,0.0000699402,0.00005367622,0.00001452507,0.000003311059,0.000008201248,0.0004195101],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3816413,"threshold_uncertainty_score":0.5594362,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2066722804","doi":"10.1016/j.geoderma.2013.09.016","title":"Predictive soil parent material mapping at a regional-scale: A Random Forest approach","year":2013,"lang":"en","type":"article","venue":"Geoderma","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":278,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Ministry of Forests; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Environment; Ministry of Forests, Lands and Natural Resource Operations","keywords":"Random forest; Digital soil mapping; Digital elevation model; Scale (ratio); Soil map; Polygon (computer graphics); Random field; Environmental science; Elevation (ballistics); Cohen's kappa; Kappa; Soil science; Computer science; Cartography; Statistics; Remote sensing; Geology; Mathematics; Artificial intelligence; Soil water; Geography; Geometry","authors":[{"name":"Brandon Heung","is_ca":true},{"name":"Chuck Bulmer","is_ca":true},{"name":"Margaret Schmidt","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01410499111385457,"gpt":0.1966404733082836,"spread":0.182535482194429,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001171888,0.0001662195,0.0001758474,0.00002675722,0.0002187174,0.00006515293,0.000181333,0.00006785389,0.001955064],"category_scores_gemma":[0.00001669104,0.0001452538,0.00005774925,0.0001010493,0.0001612499,0.0001532641,0.0002663984,0.0000788906,0.0009506337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001343927,"about_ca_system_score_gemma":0.000008318249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001895248,"about_ca_topic_score_gemma":0.0001587956,"domain_scores_codex":[0.9986537,0.00004508143,0.0002229806,0.0003619524,0.0003113487,0.0004049886],"domain_scores_gemma":[0.9994783,0.00004227594,0.00008831707,0.0002346378,0.00001296178,0.0001434638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004240236,0.0004607286,0.4917955,0.000150091,0.0001498257,0.0000377792,0.008223599,0.03104671,0.01543559,0.0002609665,0.4319793,0.02003586],"study_design_scores_gemma":[0.00254637,0.00006065848,0.8458434,0.0000400592,0.00003215259,0.00007745597,0.0006170516,0.1227352,0.0003254837,0.003675769,0.02353028,0.0005161084],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9606911,0.0000230337,0.01449942,0.0003029786,0.0002302093,0.0005664289,0.00003782986,0.00007675338,0.02357225],"genre_scores_gemma":[0.995325,0.00001972845,0.002068921,0.0004103251,0.0001536412,0.0003118034,0.0001227522,0.00001885702,0.001569019],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.408449,"threshold_uncertainty_score":0.9998273,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3011780324","doi":"10.1016/j.jag.2020.102111","title":"Regional soil organic carbon prediction model based on a discrete wavelet analysis of hyperspectral satellite data","year":2020,"lang":"en","type":"article","venue":"International Journal of Applied Earth Observation and Geoinformation","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":215,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Agriculture and Agri-Food Canada","funders":"National Natural Science Foundation of China","keywords":"Hyperspectral imaging; Principal component analysis; Remote sensing; Discrete wavelet transform; Correlation coefficient; Support vector machine; Pattern recognition (psychology); Random forest; Wavelet; Artificial intelligence; Mathematics; Wavelet transform; Computer science; Geography; Statistics","authors":[{"name":"Xiangtian Meng","is_ca":false},{"name":"Yilin Bao","is_ca":false},{"name":"Jiangui Liu","is_ca":true},{"name":"Huanjun Liu","is_ca":false},{"name":"Xinle Zhang","is_ca":false},{"name":"Yu Zhang","is_ca":false},{"name":"Peng Wang","is_ca":false},{"name":"Haitao Tang","is_ca":false},{"name":"Fanchang Kong","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02926643375017178,"gpt":0.2316717864935418,"spread":0.20240535274337,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002697294,0.00009030921,0.0001556139,0.0001460008,0.00003444967,0.00004146446,0.00023323,0.00004107792,0.00008441534],"category_scores_gemma":[0.00006079715,0.00008253342,0.00004601131,0.0003156815,0.0000409086,0.0004057683,0.00006445674,0.0001085123,0.000004066439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003962549,"about_ca_system_score_gemma":0.00003526577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002635265,"about_ca_topic_score_gemma":0.00002753768,"domain_scores_codex":[0.998621,0.00001054915,0.0005124344,0.0001242353,0.0006487013,0.00008300766],"domain_scores_gemma":[0.999158,0.00004538361,0.0005058014,0.0001203268,0.00009244542,0.00007803758],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004670151,0.00004203288,0.007190886,0.00001359412,0.0002726645,0.00000150629,0.001899551,0.9631138,0.004706023,0.001554022,0.0002496215,0.02048928],"study_design_scores_gemma":[0.0004938834,0.00005728861,0.09543947,0.00001085511,0.0001056822,0.000001401892,0.0001436592,0.9025506,0.000319892,0.0002178048,0.0005949446,0.00006449084],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9196171,0.000008805982,0.07388357,0.002728337,0.00009235369,0.0001196884,0.0001411372,0.00001477531,0.003394261],"genre_scores_gemma":[0.9907225,0.00007555493,0.007166152,0.001458414,0.0000561734,0.000001016029,0.0005054049,0.000004947693,0.000009852905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08824858,"threshold_uncertainty_score":0.3365615,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2107431407","doi":"10.1023/a:1021193827501","title":"Conditional Independence Test for Weights-of-Evidence Modeling","year":2002,"lang":"en","type":"article","venue":"Natural Resources Research","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":205,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University; Geological Survey of Canada","funders":"","keywords":"Mathematics; Independence (probability theory); Statistics; Conditional independence; Posterior probability; Event (particle physics); Conditional probability; Binary number; Statistical hypothesis testing; Combinatorics; Algorithm; Arithmetic","authors":[{"name":"Frederik P. Agterberg","is_ca":true},{"name":"Qiuming Cheng","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2017905416628054,"gpt":0.3837335256005078,"spread":0.1819429839377025,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009440414,0.00008830383,0.0001126152,0.00009161262,0.0003103647,0.00005014865,0.000436438,0.00007890347,0.001273398],"category_scores_gemma":[0.003083756,0.00006596804,0.00004970974,0.0003718603,0.0003217944,0.0001884728,0.0002558649,0.0004222934,0.000203097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000110134,"about_ca_system_score_gemma":0.000009780635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000340319,"about_ca_topic_score_gemma":0.00005246922,"domain_scores_codex":[0.9976681,0.00006277008,0.0002017933,0.0003144859,0.001328562,0.0004243188],"domain_scores_gemma":[0.9974595,0.002070772,0.00004435025,0.0001925299,0.0001309292,0.0001019031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006050841,0.001226518,0.1572964,0.0008105076,0.000142033,0.000133184,0.01368319,0.05633682,0.1444653,0.0172142,0.1342551,0.4738317],"study_design_scores_gemma":[0.0002710188,0.0001655442,0.006691942,0.000100561,0.000004695661,0.000008148619,0.0001869293,0.9610053,0.0009783471,0.009275354,0.021147,0.000165158],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9778537,0.002357492,0.004614427,0.001604953,0.0001411151,0.000815539,0.00008643309,0.00004595806,0.01248043],"genre_scores_gemma":[0.9929096,0.0001168963,0.003095629,0.00004579028,0.00007356602,0.00003824746,0.000006030979,0.000009886252,0.003704355],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9046685,"threshold_uncertainty_score":0.9996396,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1934353085","doi":"10.1111/ejss.12272","title":"Prediction of soil organic matter using a spatially constrained local partial least squares regression and the <scp>C</scp> hinese vis– <scp>NIR</scp> spectral library","year":2015,"lang":"en","type":"article","venue":"European Journal of Soil Science","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":195,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Program for New Century Excellent Talents in University; National Natural Science Foundation of China; Commonwealth Scientific and Industrial Research Organisation","keywords":"Partial least squares regression; Calibration; Local regression; Zoning; Regression analysis; Regression; Soil organic matter; Spectral space; Linear regression; Statistics; Mathematics; Environmental science; Soil science; Soil water","authors":[{"name":"Wenjun Ji","is_ca":true},{"name":"Raphael A. Viscarra Rossel","is_ca":false},{"name":"Songchao Chen","is_ca":false},{"name":"Yue Zhou","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01812606898197605,"gpt":0.2133699128800246,"spread":0.1952438438980485,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002497573,0.0001954387,0.0002605051,0.0001078811,0.0002923327,0.0002122973,0.0005963304,0.00002804842,0.00007091054],"category_scores_gemma":[0.0008621273,0.000124399,0.00006864236,0.0005312571,0.002858112,0.0009831724,0.000456181,0.0002841164,0.00004695607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007245697,"about_ca_system_score_gemma":0.0002071907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009247772,"about_ca_topic_score_gemma":0.0000122461,"domain_scores_codex":[0.9973972,0.0003585053,0.0006080695,0.0002970388,0.0009332236,0.0004059496],"domain_scores_gemma":[0.9984478,0.0002336733,0.0006415082,0.0002174154,0.00007543372,0.0003842195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002806367,0.0006267223,0.5557165,0.0001419767,0.0001334219,0.001290952,0.03711917,0.09647002,0.2411231,0.0008482338,0.03692389,0.02932539],"study_design_scores_gemma":[0.006982573,0.001274058,0.7569512,0.0007421171,0.0001739218,0.002227827,0.007606587,0.2020135,0.01717939,0.001785018,0.002874955,0.0001888218],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9764378,0.0001263567,0.01237755,0.0001970294,0.0004367629,0.0001050282,0.00001263391,0.00001667676,0.01029016],"genre_scores_gemma":[0.9976642,0.00003649043,0.00167863,0.0001856243,0.0002397883,3.826967e-7,0.000001315248,0.00002343146,0.0001702021],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2239437,"threshold_uncertainty_score":0.9998555,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2815885864","doi":"10.1111/ejss.12687","title":"Spatial modelling with Euclidean distance fields and machine learning","year":2018,"lang":"en","type":"article","venue":"European Journal of Soil Science","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":195,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Northern Alberta Institute of Technology","funders":"Deutsche Forschungsgemeinschaft","keywords":"Kriging; Random forest; Artificial intelligence; Multivariate adaptive regression splines; Support vector machine; Spatial analysis; Computer science; Mars Exploration Program; Machine learning; Regression analysis; Data mining; Mathematics; Algorithm; Statistics; Bayesian multivariate linear regression","authors":[{"name":"Karsten Schmidt","is_ca":false},{"name":"Raphael A. Viscarra Rossel","is_ca":false},{"name":"Philipp Gries","is_ca":false},{"name":"Thomas Scholten","is_ca":false},{"name":"R.A. MacMillan","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01477669742597591,"gpt":0.2045225660307896,"spread":0.1897458686048137,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001358728,0.00008018674,0.0000883399,0.00004072385,0.0003617721,0.00009689102,0.0002818296,0.000006301243,0.0000905542],"category_scores_gemma":[0.00006563558,0.00005772715,0.00001420198,0.0002261304,0.0009116447,0.0002744565,0.000148277,0.0001840109,0.00003282102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000291365,"about_ca_system_score_gemma":0.00001921127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001686144,"about_ca_topic_score_gemma":0.0001243929,"domain_scores_codex":[0.9989574,0.00006092868,0.0001946664,0.0001726354,0.0004034023,0.0002109767],"domain_scores_gemma":[0.9994782,0.00003042494,0.0001967922,0.00009188625,0.0000457971,0.000156856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003057336,0.0001101402,0.3100219,0.0000239819,0.00002657463,0.0007948381,0.01108184,0.2261858,0.007447989,0.001380374,0.0005816369,0.4420392],"study_design_scores_gemma":[0.001526335,0.003011153,0.2327973,0.0002996313,0.00004276186,0.0007008651,0.0005400894,0.7093188,0.002176375,0.0009622626,0.04796405,0.0006604593],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5255731,0.00003099711,0.4539815,0.0001028172,0.00009050437,0.00001820062,5.494653e-7,0.000006141872,0.02019614],"genre_scores_gemma":[0.9878205,0.00003625108,0.01174668,0.00009515566,0.0001090012,6.900149e-8,1.145095e-7,0.000008272939,0.000183956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.483133,"threshold_uncertainty_score":0.3358993,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4220943881","doi":"10.1101/2022.03.24.485545","title":"sdmTMB: An R Package for Fast, Flexible, and User-Friendly Generalized Linear Mixed Effects Models with Spatial and Spatiotemporal Random Fields","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":183,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Computer science; R package; Random effects model; Mathematics; Computational science","authors":[{"name":"Sean C. Anderson","is_ca":true},{"name":"Eric J. Ward","is_ca":false},{"name":"Philina A. English","is_ca":true},{"name":"Lewis A. K. Barnett","is_ca":false},{"name":"James T. Thorson","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01146466889708274,"gpt":0.2179257944969149,"spread":0.2064611255998322,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005490288,0.0005129814,0.0005972045,0.0001028647,0.0003672681,0.0002020281,0.0003119088,0.000281509,0.00007133579],"category_scores_gemma":[0.00008953009,0.0004995404,0.00006691291,0.0001852334,0.0001976798,0.0002371871,0.0007585005,0.0004427308,0.000002839181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001169022,"about_ca_system_score_gemma":0.00009668927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00151586,"about_ca_topic_score_gemma":0.0001188516,"domain_scores_codex":[0.9974363,0.0001782072,0.0003729736,0.00111389,0.0004000959,0.0004984687],"domain_scores_gemma":[0.9984236,0.0001548139,0.0003007611,0.0007295532,0.00005669165,0.0003346165],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01116284,0.002770152,0.2757249,0.01118851,0.002609383,0.001195632,0.001481277,0.1378499,0.5185906,0.02468087,0.01121258,0.001533389],"study_design_scores_gemma":[0.02723842,0.00320138,0.3053912,0.0008247998,0.001147411,4.340048e-7,0.00005627421,0.5267263,0.1124825,0.0002882624,0.016783,0.005860009],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6840081,0.000188164,0.3135635,0.00006052541,0.0003680429,0.001323594,0.0003429744,0.0001344722,0.00001069647],"genre_scores_gemma":[0.8999208,0.0001385915,0.09892198,0.0001668221,0.0001705611,0.0005564755,0.00000543476,0.0001021706,0.00001713917],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.406108,"threshold_uncertainty_score":0.9997456,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1492244543","doi":"10.2134/agronmonogr44.c26","title":"Application in Analysis of Soils","year":2004,"lang":"en","type":"book-chapter","venue":"Agronomy monograph/Agronomy","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":179,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Pacific Safety Products (Canada)","funders":"","keywords":"Soil water; Near-infrared spectroscopy; Environmental science; Soil test; Soil science; Spectroscopy; Near infrared reflectance spectroscopy; Physics; Optics","authors":[{"name":"D. F. Malley","is_ca":true},{"name":"P. D. Martin","is_ca":false},{"name":"Eyal Ben‐Dor","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.00982547040704313,"gpt":0.2111885956770345,"spread":0.2013631252699914,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002956122,0.0004801681,0.000825597,0.0008871985,0.00008428274,0.00003859382,0.0004501949,0.0003106434,0.003184168],"category_scores_gemma":[0.000005671135,0.0005302895,0.0004969217,0.0005777727,0.0004205528,0.0001903398,0.0002422074,0.0003020226,0.0002317784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003554997,"about_ca_system_score_gemma":0.00005296413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004595057,"about_ca_topic_score_gemma":0.001978593,"domain_scores_codex":[0.997539,0.00002107992,0.0008532332,0.0008512168,0.000317303,0.0004182012],"domain_scores_gemma":[0.9983431,0.00009593945,0.0006128041,0.0007682462,0.00002280114,0.0001571178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007850961,0.0003573765,0.3436915,0.0001466723,0.004353205,0.00002833668,0.002044534,0.08022884,0.00005148983,0.3360495,0.005310081,0.2276599],"study_design_scores_gemma":[0.001847222,0.0001497461,0.5096335,0.0004013003,0.0041277,0.00000288914,0.0002440046,0.002631429,0.00009230813,0.2008077,0.2771159,0.002946316],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01661868,0.0009687987,0.0149584,0.00007857275,0.00006919508,0.001129586,0.00009931263,0.00006562239,0.9660118],"genre_scores_gemma":[0.9506874,0.0005591343,0.01332704,0.0001397557,0.00005918921,0.0003166625,0.0009076456,0.0001108184,0.03389231],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9340687,"threshold_uncertainty_score":0.9997149,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1486009484","doi":"10.1002/9781118445112.stat07766.pub2","title":"Spatial Analysis in Ecology","year":2016,"lang":"en","type":"other","venue":"Wiley StatsRef: Statistics Reference Online","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":176,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Northern British Columbia; University of Toronto","funders":"","keywords":"Spatial analysis; Autocorrelation; Spatial ecology; Ecology; Macroecology; Common spatial pattern; Sampling (signal processing); Mesoscale meteorology; Spatial correlation; Geography; Temporal scales; Spatial dependence; Statistics; Computer science; Mathematics; Remote sensing; Biogeography; Biology; Meteorology","authors":[{"name":"Marie‐Josée Fortin","is_ca":true},{"name":"Mark R. T. Dale","is_ca":true},{"name":"Jay M. Ver Hoef","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01805152306611417,"gpt":0.2876200429536096,"spread":0.2695685198874954,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001923861,0.0005124267,0.000848809,0.0005780525,0.00005721748,0.00003627788,0.0005103967,0.0003833576,0.06834059],"category_scores_gemma":[0.0001871523,0.000439207,0.00007195816,0.0005766336,0.0003777267,0.00003980033,0.0003532332,0.0004074553,0.002448733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003207664,"about_ca_system_score_gemma":0.00009161374,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01357579,"about_ca_topic_score_gemma":0.2347042,"domain_scores_codex":[0.9970076,0.0001442561,0.000642796,0.0009102945,0.0005494929,0.0007455685],"domain_scores_gemma":[0.9983529,0.0002685746,0.0004877212,0.0006335534,0.00002508226,0.0002322066],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004360282,0.0004424202,0.07660753,0.00007197239,0.0004879539,0.0003298201,0.00009509927,0.0001800128,0.00003737371,0.005512041,0.7809035,0.1352887],"study_design_scores_gemma":[0.001066292,0.000172921,0.1004559,0.0001885439,0.0005530421,0.000003896526,0.00003852774,0.003837283,0.000002293809,0.009306673,0.883203,0.001171619],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0004370442,0.0002280494,0.3940383,0.0002061557,0.0009350342,0.0009427358,0.07968584,0.0002832205,0.5232437],"genre_scores_gemma":[0.01115226,0.004490749,0.1801398,0.0004818722,0.0003867781,0.00009811671,0.01213309,0.000694327,0.790423],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2671793,"threshold_uncertainty_score":0.999806,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2626828989","doi":"10.1016/j.grj.2017.06.001","title":"Soil legacy data rescue via GlobalSoilMap and other international and national initiatives","year":2017,"lang":"en","type":"article","venue":"GeoResJ","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":174,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Agriculture and Agri-Food Canada","funders":"European Commission; Bill and Melinda Gates Foundation","keywords":"Database; Computer science; Data science","authors":[{"name":"Dominique Arrouays","is_ca":false},{"name":"J.G.B. Leenaars","is_ca":false},{"name":"Anne C Richer-De-Forges","is_ca":false},{"name":"Kabindra Adhikari","is_ca":false},{"name":"Cristiano Ballabio","is_ca":false},{"name":"Mogens Humlekrog Greve","is_ca":false},{"name":"Mike Grundy","is_ca":false},{"name":"Eliseo Guerrero","is_ca":false},{"name":"Jon Hempel","is_ca":false},{"name":"Tomislav Hengl","is_ca":false},{"name":"G.B.M. Heuvelink","is_ca":false},{"name":"N.H. Batjes","is_ca":false},{"name":"Eloi Carvalho","is_ca":false},{"name":"Alfred E. Hartemink","is_ca":false},{"name":"Alan J. Hewitt","is_ca":false},{"name":"Suk-Young Hong","is_ca":false},{"name":"Pavel Krasilnikov","is_ca":false},{"name":"Philippe Lagacherie","is_ca":false},{"name":"Glen Lelyk","is_ca":true},{"name":"Zamir Libohova","is_ca":false},{"name":"Allan Lilly","is_ca":false},{"name":"Alex B. McBratney","is_ca":false},{"name":"N. J. McKenzie","is_ca":false},{"name":"Gustavo M. Vasquez","is_ca":false},{"name":"Vera Leatitia Mulder","is_ca":false},{"name":"Budiman Minasny","is_ca":false},{"name":"Luca Montanarella","is_ca":false},{"name":"Inakwu Odeh","is_ca":false},{"name":"José Padarian","is_ca":false},{"name":"Laura Poggio","is_ca":false},{"name":"Pierre Roudier","is_ca":false},{"name":"Nicolas Saby","is_ca":false},{"name":"I. Yu. Savin","is_ca":false},{"name":"Ross Searle","is_ca":false},{"name":"Vladimir Solbovoy","is_ca":false},{"name":"James A. Thompson","is_ca":false},{"name":"Scott Smith","is_ca":true},{"name":"Yiyi Sulaeman","is_ca":false},{"name":"Ruxandra Vintilă","is_ca":false},{"name":"Raphael A. Viscarra Rossel","is_ca":false},{"name":"Peter Wilson","is_ca":false},{"name":"Gan‐Lin Zhang","is_ca":false},{"name":"M. Swerts","is_ca":false},{"name":"Katrien Oorts","is_ca":false},{"name":"A. Kārkliņš","is_ca":false},{"name":"Feng Liu","is_ca":false},{"name":"Alexandro R. Ibelles Navarro","is_ca":false},{"name":"Arkadiy Levin","is_ca":false},{"name":"Tetiana Laktionova","is_ca":false},{"name":"Martin Dell'Acqua","is_ca":false},{"name":"Nopmanee Suvannang","is_ca":false},{"name":"Waew Ruam","is_ca":false},{"name":"Jagdish Prasad","is_ca":false},{"name":"N. G. Patil","is_ca":false},{"name":"Stjepan Husnjak","is_ca":false},{"name":"László Pásztor","is_ca":false},{"name":"J. P. Okx","is_ca":false},{"name":"Stephen Hallett","is_ca":false},{"name":"C. A. Keay","is_ca":false},{"name":"Timothy S. Farewell","is_ca":false},{"name":"Harri Lilja","is_ca":false},{"name":"Jérôme Juilleret","is_ca":false},{"name":"Simone Marx","is_ca":false},{"name":"Yusuke Takata","is_ca":false},{"name":"K. Yagi","is_ca":false},{"name":"Nicolas Mansuy","is_ca":false},{"name":"Panos Panagos","is_ca":false},{"name":"Mark Van Liedekerke","is_ca":false},{"name":"Rastislav Skalský","is_ca":false},{"name":"Jaroslava Sobocká","is_ca":false},{"name":"Josef Kobza","is_ca":false},{"name":"Kamran Eftekhari","is_ca":false},{"name":"Seyed Kazem Alavipanah","is_ca":false},{"name":"Rachid Moussadek","is_ca":false},{"name":"Mohamed Badraoui","is_ca":false},{"name":"Mayesse Da Silva","is_ca":false},{"name":"Garry Paterson","is_ca":false},{"name":"M. C. Gonçalves","is_ca":false},{"name":"Sid Theocharopoulos","is_ca":false},{"name":"Martin Yemefack","is_ca":false},{"name":"Silatsa Tedou","is_ca":false},{"name":"Borut Vrščaj","is_ca":false},{"name":"Urs Grob","is_ca":false},{"name":"Josef Kozák","is_ca":false},{"name":"Luboš Borůvka","is_ca":false},{"name":"Endre Dobos","is_ca":false},{"name":"Miguel Ángel Taboada","is_ca":false},{"name":"Lucas M. Moretti","is_ca":false},{"name":"Dario Rodríguez","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03920970807795823,"gpt":0.3078302376910173,"spread":0.268620529613059,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002267375,0.00006577073,0.00005623498,0.000013723,0.000254672,0.0002100024,0.000352167,0.00002529251,0.0003546836],"category_scores_gemma":[0.0002585807,0.00006080567,0.000005938727,0.00001320917,0.0002862571,0.0005932474,0.0009366988,0.00004735522,0.00006152114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001983227,"about_ca_system_score_gemma":0.000008224593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001617171,"about_ca_topic_score_gemma":0.0008522203,"domain_scores_codex":[0.9993402,0.00001310124,0.0000836481,0.0002422551,0.0002130373,0.0001077434],"domain_scores_gemma":[0.9995824,0.0000358763,0.00005707834,0.0002641488,0.000009873113,0.0000506973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006351768,0.0001121537,0.7449384,0.00002153729,0.0001208056,0.00003477862,0.001255194,0.0001584062,0.001427592,0.05207667,0.03101913,0.1687718],"study_design_scores_gemma":[0.0003453582,0.00001084086,0.8758705,0.00001142748,0.000005196785,0.00001333203,0.00006337333,0.01258956,0.0000319699,0.01567334,0.09526901,0.0001161192],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6056374,0.0001257034,0.002262792,0.003235562,0.0004975974,0.0001582459,0.0007308006,0.00003295826,0.3873189],"genre_scores_gemma":[0.9973974,0.00004308242,0.001592066,0.0004678888,0.00009112341,0.000002933956,0.00003357862,0.000005406697,0.0003664721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.39176,"threshold_uncertainty_score":0.3883536,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3010020030","doi":"10.1016/j.scitotenv.2020.137703","title":"Improved digital soil mapping with multitemporal remotely sensed satellite data fusion: A case study in Iran","year":2020,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":155,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; University of Zanjan","keywords":"Covariate; Digital soil mapping; Digital elevation model; Environmental science; Terrain; Satellite imagery; Satellite; Soil carbon; Remote sensing; Random forest; Normalized Difference Vegetation Index; Soil science; Soil map; Computer science; Soil water; Statistics; Geology; Cartography; Climate change; Geography; Mathematics; Artificial intelligence","authors":[{"name":"Solmaz Fathololoumi","is_ca":true},{"name":"Ali Reza Vaezi","is_ca":false},{"name":"Seyed Kazem Alavipanah","is_ca":false},{"name":"Daniel D. Saurette","is_ca":true},{"name":"Asim Biswas","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04265170420994852,"gpt":0.2338115680383415,"spread":0.191159863828393,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006477344,0.0001714477,0.0001660878,0.00002292889,0.0003149765,0.00008283248,0.001113166,0.00002000111,0.00006319565],"category_scores_gemma":[0.00008404472,0.0000953277,0.00002949964,0.0005195746,0.001265058,0.000365136,0.002637832,0.0001752205,0.00003765186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001087495,"about_ca_system_score_gemma":0.00002413801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001307623,"about_ca_topic_score_gemma":0.00008903313,"domain_scores_codex":[0.9979998,0.00006218299,0.0003001194,0.0005854364,0.0007109081,0.0003415726],"domain_scores_gemma":[0.9986026,0.00005663575,0.0001710745,0.001039046,0.000002732022,0.0001278559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005400441,0.002072664,0.06571639,0.00007517076,0.0001049444,0.002294569,0.1017389,0.3407691,0.3734593,0.00003196582,0.0001895931,0.1130074],"study_design_scores_gemma":[0.002483422,0.0008305761,0.2881599,0.0000650213,0.00006219327,0.0007938629,0.03920049,0.664655,0.002561882,0.00009318633,0.0003768946,0.0007175878],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975659,0.00001504289,0.0001779658,0.0008895391,0.00005163468,0.0006811894,0.00003209305,0.00001182879,0.0005748255],"genre_scores_gemma":[0.9988819,0.000004581375,0.0008978152,0.00006210925,0.00001795937,0.000004775154,0.000002564302,0.00001102409,0.0001172725],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3708974,"threshold_uncertainty_score":0.4661159,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2551325900","doi":"10.1016/j.catena.2016.10.017","title":"Exploring the spatial variability of soil properties in an Alfisol soil catena","year":2016,"lang":"en","type":"article","venue":"CATENA","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":149,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Winnipeg","funders":"University of Peradeniya; National Research Council Sri Lanka","keywords":"Alfisol; Cation-exchange capacity; Soil science; Topsoil; Soil carbon; Spatial variability; Environmental science; Variogram; Soil pH; Kriging; Soil map; Geostatistics; Soil test; Soil texture; Spatial heterogeneity; Soil survey; Digital soil mapping; Soil water; Mathematics; Ecology","authors":[{"name":"F. Rosemary","is_ca":false},{"name":"U.W.A. Vitharana","is_ca":false},{"name":"Srimathie P. Indraratne","is_ca":true},{"name":"Rohan Weerasooriya","is_ca":false},{"name":"Umakant Mishra","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06721147568495585,"gpt":0.2181943426913136,"spread":0.1509828670063578,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004406018,0.00009320513,0.0001148201,0.00001751938,0.0000647742,0.00001270479,0.0002296833,0.00002310988,0.000122713],"category_scores_gemma":[0.0001682929,0.00004686719,0.00002366901,0.00009240395,0.0002550562,0.000229882,0.0001489007,0.00005827707,0.00006382271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008162408,"about_ca_system_score_gemma":0.00001815267,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008011871,"about_ca_topic_score_gemma":0.003112169,"domain_scores_codex":[0.9990821,0.00008117892,0.0002081133,0.0002279571,0.0001681856,0.0002324543],"domain_scores_gemma":[0.9994838,0.00007147319,0.00005680891,0.0003204883,0.00001310908,0.00005431036],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008283026,0.0002970388,0.4843605,0.00005316699,0.00001487698,0.00001039153,0.007013863,0.001906219,0.1999474,0.0005779493,0.0002353493,0.3055005],"study_design_scores_gemma":[0.0004530306,0.00009601648,0.9557402,0.00005907013,0.00001092104,0.000002676203,0.000324226,0.003422581,0.03586305,0.003119207,0.0006801857,0.000228896],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968282,0.000006801821,0.0009432971,0.0004191269,0.0001576264,0.0001351776,0.000006690945,0.00001696698,0.001486109],"genre_scores_gemma":[0.9996302,0.00002397818,0.00006278261,0.00004665337,0.00003619691,0.0000587445,0.000001247649,0.000009425822,0.0001308271],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4713797,"threshold_uncertainty_score":0.9985939,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2135330788","doi":"10.1111/rssb.12009","title":"Spatial Spline Regression Models","year":2013,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series B (Statistical Methodology)","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":145,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Division of Mathematical Sciences; Natural Sciences and Engineering Research Council of Canada; Politecnico di Milano; Regione Lombardia; Ministero dell’Istruzione, dell’Università e della Ricerca","keywords":"Spline (mechanical); Covariate; Spatial analysis; Piecewise; Computer science; Segmented regression; Quadratic equation; Regression analysis; Regression; Algorithm; Mathematics; Data mining; Polynomial regression; Statistics; Geometry; Mathematical analysis; Engineering","authors":[{"name":"Laura M. Sangalli","is_ca":false},{"name":"J. O. Ramsay","is_ca":true},{"name":"Tim Ramsay","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04538228599086537,"gpt":0.2980646095571556,"spread":0.2526823235662903,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001568319,0.0003277851,0.0006581377,0.00001876301,0.0003900929,0.00009707696,0.0006407024,0.0002238831,0.007601366],"category_scores_gemma":[0.003830216,0.0001967783,0.0002639731,0.0002042022,0.001307003,0.000251357,0.0005913155,0.0008531871,0.0001620437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002081944,"about_ca_system_score_gemma":0.00006034883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001193791,"about_ca_topic_score_gemma":0.00004319465,"domain_scores_codex":[0.9962635,0.0008956782,0.001000714,0.000356452,0.0008484499,0.0006351893],"domain_scores_gemma":[0.995214,0.003334332,0.0005526852,0.0003330996,0.0001328764,0.000433034],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006106978,0.0005376345,0.007158473,0.0001570137,0.00041761,0.0001411445,0.001569687,0.01776225,0.002691849,0.1415918,0.5695143,0.2578476],"study_design_scores_gemma":[0.001085826,0.0006982331,0.1117913,0.00008154265,0.0002770141,0.0001758298,0.0004928309,0.1497187,0.0002978518,0.7229733,0.01185654,0.0005509607],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00762434,0.00005332058,0.9868587,0.00224743,0.0009783948,0.0002796894,0.0001774262,0.00001925223,0.001761432],"genre_scores_gemma":[0.135574,0.00004027537,0.8619871,0.001017591,0.0002685103,0.00001431141,0.00001126961,0.00003535957,0.001051582],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5813816,"threshold_uncertainty_score":0.9933058,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2059542853","doi":"10.1016/j.geoderma.2014.06.032","title":"Digital mapping of soil properties in Canadian managed forests at 250m of resolution using the k-nearest neighbor method","year":2014,"lang":"en","type":"article","venue":"Geoderma","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":145,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Natural Resources Canada; Canadian Forest Service","funders":"U.S. Geological Survey; National Aeronautics and Space Administration","keywords":"Soil map; Environmental science; Mean squared error; Soil texture; Digital soil mapping; Scale (ratio); Soil science; Hydrology (agriculture); Physical geography; Soil water; Statistics; Mathematics; Geography; Cartography; Geology","authors":[{"name":"Nicolas Mansuy","is_ca":true},{"name":"Évelyne Thiffault","is_ca":true},{"name":"David Paré","is_ca":true},{"name":"Pierre Y. Bernier","is_ca":true},{"name":"Luc Guindon","is_ca":true},{"name":"Philippe Villemaire","is_ca":true},{"name":"Vincent Poirier","is_ca":true},{"name":"André Beaudoin","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02371114405044822,"gpt":0.2289416690899809,"spread":0.2052305250395327,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003516992,0.00007744025,0.0001173624,0.00005750355,0.0001101412,0.00001838285,0.0001495783,0.00003599739,0.00004261137],"category_scores_gemma":[0.0001284145,0.00005917175,0.00002740304,0.0001648717,0.0001315875,0.0001061909,0.0001467404,0.00006000272,0.000009484544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001545955,"about_ca_system_score_gemma":0.00002309027,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.287438,"about_ca_topic_score_gemma":0.4819411,"domain_scores_codex":[0.9991525,0.00006040115,0.0002046433,0.0001419022,0.0001636155,0.0002769833],"domain_scores_gemma":[0.9995944,0.00005585141,0.00008882207,0.0001877934,0.000009736044,0.00006335638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002096234,0.00003132009,0.8050507,0.00009293405,0.00001649119,0.000007495986,0.002403124,0.1435836,0.007361798,0.00055138,0.0003281755,0.04055213],"study_design_scores_gemma":[0.0001493012,0.00001247975,0.5725812,0.00005027563,0.000005510823,0.000005367797,0.0002020768,0.4237395,0.0007612949,0.0004625972,0.001944791,0.00008558244],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9826533,0.00003011719,0.008431378,0.0001532836,0.00004920201,0.0001481979,0.00001616081,0.000005648153,0.008512751],"genre_scores_gemma":[0.9980456,0.00000238778,0.001654965,0.00005974725,0.00001237446,0.000004354681,0.000004725778,0.000007979294,0.0002079253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.280156,"threshold_uncertainty_score":0.717307,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1993304724","doi":"10.1007/s11004-009-9258-9","title":"High-order Statistics of Spatial Random Fields: Exploring Spatial Cumulants for Modeling Complex Non-Gaussian and Non-linear Phenomena","year":2009,"lang":"en","type":"article","venue":"Mathematical Geosciences","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":144,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Cumulant; Geostatistics; Spatial analysis; Gaussian; Spatial dependence; Random field; Statistical physics; Spatial variability; Spatial ecology; Spatial correlation; Mathematics; Field (mathematics); Statistics; Physics","authors":[{"name":"Roussos Dimitrakopoulos","is_ca":true},{"name":"Hussein Mustapha","is_ca":true},{"name":"Erwan Gloaguen","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05169258426671069,"gpt":0.278309367307605,"spread":0.2266167830408943,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004074116,0.0001690856,0.0003501764,0.00004378771,0.000213477,0.00005239257,0.0002268111,0.000044821,0.0002423803],"category_scores_gemma":[0.0002522792,0.0001351866,0.00003401349,0.0001316805,0.0002406025,0.0001489295,0.0001052481,0.00007539492,0.0000169395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001779017,"about_ca_system_score_gemma":0.00001653603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00128273,"about_ca_topic_score_gemma":0.0001396944,"domain_scores_codex":[0.9984448,0.00001716476,0.0004329768,0.0003372915,0.0003967152,0.0003710743],"domain_scores_gemma":[0.9993156,0.000234486,0.0001172439,0.0001683412,0.00002740744,0.0001368793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006954946,0.002116211,0.003802522,0.001249519,0.0001202549,0.00004364653,0.0221705,0.2214767,0.01881729,0.04472211,0.001033207,0.6837525],"study_design_scores_gemma":[0.0008481481,0.0002319636,0.003219812,0.00004589487,0.00002152252,0.000001846788,0.0002508677,0.9458076,0.0001839749,0.04916199,0.00004500354,0.0001814042],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1915905,0.000004061068,0.8071244,0.0001207148,0.0001117225,0.0003155032,0.00005539483,0.00001315123,0.0006644693],"genre_scores_gemma":[0.8030478,0.00001376945,0.1967009,0.00008407777,0.00006724794,0.0000227721,0.000009206769,0.000006805232,0.00004744928],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7243308,"threshold_uncertainty_score":0.551275,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2021883703","doi":"10.1080/13658810600894364","title":"DEM resolution dependencies of terrain attributes across a landscape","year":2007,"lang":"en","type":"article","venue":"International Journal of Geographical Information Systems","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":144,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Landform; Terrain; Sample (material); Cluster analysis; Resampling; Curvature; Topographic Wetness Index; Orientation (vector space); Sampling (signal processing); Geography; Cartography; Geology; Remote sensing; Mathematics; Digital elevation model; Statistics; Computer science; Geometry; Computer vision","authors":[{"name":"Yinan Deng","is_ca":false},{"name":"John P. Wilson","is_ca":false},{"name":"Bernard O. Bauer","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01204847211418065,"gpt":0.2686715728666286,"spread":0.256623100752448,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001804487,0.00007846134,0.0001503699,0.0001861256,0.00005452139,0.00008262252,0.0002639017,0.00007359742,0.00006410113],"category_scores_gemma":[0.0002627427,0.00006461074,0.0001010044,0.0002347309,0.0001028002,0.000808236,0.00009477813,0.0001380568,0.00002606862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006236884,"about_ca_system_score_gemma":0.00001323328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003270273,"about_ca_topic_score_gemma":0.00006105415,"domain_scores_codex":[0.9978649,0.00002841542,0.0009502755,0.00005180697,0.000934617,0.0001699794],"domain_scores_gemma":[0.9985779,0.0001482538,0.0007977189,0.00007244595,0.0003157196,0.00008796919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000460508,0.0001541192,0.9262258,0.000055772,0.0003154799,0.00004702904,0.005473955,0.01932061,0.00164027,0.007430449,0.006909094,0.03196689],"study_design_scores_gemma":[0.001474923,0.0002378087,0.9100304,0.0002051232,0.00002195085,0.0007488582,0.005695796,0.01049196,0.0005138752,0.000667321,0.06967996,0.0002319844],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8448759,0.0001086891,0.1495856,0.0002522757,0.00127951,0.0001091425,0.00007211245,0.00001324429,0.003703595],"genre_scores_gemma":[0.9989479,0.00003370871,0.0007941694,0.0000832353,0.0001036057,0.000001279211,0.00001764438,0.000002736316,0.00001571553],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.154072,"threshold_uncertainty_score":0.263475,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2312032020","doi":"10.1016/j.jag.2016.03.008","title":"Spatiotemporal monitoring of soil salinization in irrigated Tadla Plain (Morocco) using satellite spectral indices","year":2016,"lang":"en","type":"article","venue":"International Journal of Applied Earth Observation and Geoinformation","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":142,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Centre National pour la Recherche Scientifique et Technique; Centre National de la Recherche Scientifique","keywords":"Soil salinity; Thematic Mapper; Hydrology (agriculture); Salinity; Environmental science; Thematic map; Satellite; Spatial variability; Remote sensing; Soil water; Satellite imagery; Soil science; Geography; Geology; Cartography; Mathematics; Statistics","authors":[{"name":"Abderrazak El Harti","is_ca":false},{"name":"Rachid Lhissou","is_ca":false},{"name":"Karem Chokmani","is_ca":true},{"name":"Jamal-Eddine Ouzemou","is_ca":false},{"name":"Mohamed E. M. Hassouna","is_ca":false},{"name":"El Mostafa Bachaoui","is_ca":false},{"name":"Abderrahmène El Ghmari","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01905098605282497,"gpt":0.241523773388502,"spread":0.222472787335677,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004132256,0.00008498747,0.0001232175,0.0001735253,0.00003242446,0.00003805805,0.0001132172,0.00005224986,0.00007578366],"category_scores_gemma":[0.00005999987,0.0000685632,0.00002475796,0.0001633403,0.00004825849,0.0008830693,0.00003728935,0.00006882092,0.000007411049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008203051,"about_ca_system_score_gemma":0.00002712365,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001498998,"about_ca_topic_score_gemma":0.00007446164,"domain_scores_codex":[0.9987072,0.00001452499,0.0006695884,0.00007533674,0.0004310836,0.0001022755],"domain_scores_gemma":[0.9990195,0.00005761628,0.000736268,0.00004799457,0.00009538831,0.00004323038],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002529384,0.00004720026,0.7704354,0.00002080795,0.000042125,0.000005222576,0.002641098,0.02665219,0.0248288,0.002104461,0.00001705749,0.1729527],"study_design_scores_gemma":[0.00103917,0.00003627755,0.9700057,0.0001268351,0.00000818946,0.00001235911,0.0002242459,0.01237923,0.01350782,0.002163416,0.0003990554,0.00009774198],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900008,0.00001217145,0.008841291,0.000171643,0.0002365163,0.00008295466,0.000007344006,0.000006210487,0.0006410439],"genre_scores_gemma":[0.9908121,0.0001058131,0.008909136,0.00005337347,0.00008279824,9.913917e-7,0.00001584835,0.000005082258,0.00001486514],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1995703,"threshold_uncertainty_score":0.2795926,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2003031087","doi":"10.2136/vzj2007.0040","title":"Spatial Scaling Analyses of Soil Physical Properties: A Review of Spectral and Wavelet Methods","year":2008,"lang":"en","type":"review","venue":"Vadose Zone Journal","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":135,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Wavelet; Scaling; Soil science; Wavelet transform; Environmental science; Mathematics; Computer science; Artificial intelligence","authors":[{"name":"Bingcheng Si","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1051808338083855,"gpt":0.3933929093533073,"spread":0.2882120755449219,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006669689,0.0003073562,0.001924855,0.00009808035,0.00009924272,0.00001845449,0.0002511107,0.00008617718,0.0002446363],"category_scores_gemma":[0.0002859155,0.0002037955,0.0005060714,0.0003266719,0.0002843352,0.00007495872,0.0001957179,0.0004714201,0.000009673418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008581248,"about_ca_system_score_gemma":0.0001185264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003940381,"about_ca_topic_score_gemma":0.000006712231,"domain_scores_codex":[0.9975805,0.0004376066,0.000992606,0.0002633704,0.0004610301,0.00026483],"domain_scores_gemma":[0.9983609,0.000156416,0.001073195,0.0002219961,0.00003292798,0.0001545156],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002530054,0.00007189754,0.000007147571,0.01456864,0.0001316587,0.00002122682,0.0001122895,0.000009847578,0.00008283059,0.000003726404,0.0003382369,0.98465],"study_design_scores_gemma":[0.000574944,0.0004122702,0.0002653678,0.2252716,0.003411864,0.0033148,0.00005155517,0.002327996,0.0003720694,0.0001892986,0.7628023,0.001005907],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002079349,0.9909827,0.008034324,0.00001346323,0.00009673686,0.0002340837,0.00001622683,0.000005094471,0.000409505],"genre_scores_gemma":[0.00008477924,0.9805282,0.01908383,0.00002526777,0.0001862668,0.00000562394,0.000004788538,0.00002599367,0.0000551977],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9836441,"threshold_uncertainty_score":0.8310541,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2046000332","doi":"10.1023/b:narr.0000046916.91703.bb","title":"Minimum Acceptance Criteria for Geostatistical Realizations","year":2004,"lang":"en","type":"article","venue":"Natural Resources Research","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":133,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"University of Alberta","keywords":"Kriging; Computer science; Geostatistics; Software; Measure (data warehouse); Data mining; Mathematical optimization; Industrial engineering; Statistics; Mathematics; Engineering; Machine learning; Spatial variability","authors":[{"name":"Oy Leuangthong","is_ca":true},{"name":"Jason A. McLennan","is_ca":true},{"name":"Clayton V. Deutsch","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05822061189395763,"gpt":0.3977040138884395,"spread":0.3394834019944819,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006646066,0.0001044183,0.0001144729,0.00007631261,0.000500788,0.0001317543,0.0003690592,0.00007817453,0.0008465036],"category_scores_gemma":[0.001966419,0.00009228134,0.00004029225,0.000468741,0.0004074302,0.0001069577,0.0002528138,0.0003094113,0.0002647039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002296811,"about_ca_system_score_gemma":0.00002598513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007082908,"about_ca_topic_score_gemma":0.0003785362,"domain_scores_codex":[0.9980527,0.00007911472,0.0001882391,0.0003703286,0.0007012714,0.0006083529],"domain_scores_gemma":[0.9989182,0.0005603158,0.00002940483,0.0002386086,0.00008367829,0.0001697743],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009355609,0.0006159709,0.008157976,0.0002710332,0.00008770217,0.000175247,0.0115905,0.003881741,0.05192913,0.1394687,0.4748699,0.3080165],"study_design_scores_gemma":[0.001525935,0.000315563,0.07906249,0.00006511033,0.00001178769,0.00001685008,0.0007267004,0.0138072,0.0009388036,0.07343212,0.8296649,0.00043258],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8758513,0.000665586,0.04842769,0.00642379,0.0006658681,0.001947424,0.0003873291,0.0001705353,0.06546044],"genre_scores_gemma":[0.9751707,0.00003422439,0.01994178,0.0001853151,0.0001408197,0.00008810895,0.00005538111,0.00002104508,0.004362644],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3547949,"threshold_uncertainty_score":0.9268621,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2106308596","doi":"10.1023/a:1007570402430","title":"Geostatistical Simulation of Regionalized Pore-Size Distributions Using Min/Max Autocorrelation Factors","year":2000,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":130,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Geological Survey of Canada","funders":"","keywords":"Autocorrelation; Mathematics; Parametric statistics; Statistics; Geostatistics; Spatial correlation; Series (stratigraphy); Statistical physics; Applied mathematics; Spatial variability; Geology; Physics","authors":[{"name":"A. J. Desbarats","is_ca":true},{"name":"Roussos Dimitrakopoulos","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02582480517798217,"gpt":0.2823065324349262,"spread":0.256481727256944,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001577048,0.0001323816,0.0002526064,0.00002134742,0.0001098926,0.000009098399,0.0001037928,0.0001172238,0.02373719],"category_scores_gemma":[0.0007453789,0.0001172923,0.00006036345,0.0001692975,0.0003977302,0.00006623432,0.00005892659,0.00009861084,0.0002708495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006817484,"about_ca_system_score_gemma":0.00001327668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001546435,"about_ca_topic_score_gemma":0.000007779678,"domain_scores_codex":[0.9987736,0.00007161467,0.0004300886,0.0002260535,0.0002339293,0.0002646755],"domain_scores_gemma":[0.9984134,0.001171523,0.0001089895,0.0001915919,0.00001904094,0.00009539859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002639814,0.00143608,0.1041303,0.0002155215,0.0001469658,0.00007204641,0.00280062,0.4036158,0.001999758,0.4526734,0.002327394,0.03031814],"study_design_scores_gemma":[0.000335783,0.0000512129,0.06499702,0.00001760407,0.00004653698,0.00001470337,0.0000312771,0.7556524,0.00003930719,0.1768532,0.001804543,0.0001564388],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5655749,0.000003865278,0.4292429,0.00009056316,0.00003739119,0.0002064077,0.0000359687,0.00002925026,0.004778697],"genre_scores_gemma":[0.9698033,0.000001545656,0.02929872,0.00003814257,0.00001433175,0.000008536111,0.00009319895,0.00001015594,0.0007320601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4042283,"threshold_uncertainty_score":0.9771553,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2053522515","doi":"10.1007/s11119-008-9080-2","title":"A comparison of crop data measured by two commercial sensors for variable-rate nitrogen application","year":2008,"lang":"en","type":"article","venue":"Precision Agriculture","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":129,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Normalized Difference Vegetation Index; Agronomy; Crop; Environmental science; Precision agriculture; Biomass (ecology); Nitrogen; Combine harvester; Fertilizer; Mathematics; Remote sensing; Leaf area index; Geography; Biology; Chemistry","authors":[{"name":"Nicolas Tremblay","is_ca":true},{"name":"Zhijie Wang","is_ca":true},{"name":"B. L.","is_ca":true},{"name":"C. Bélec","is_ca":true},{"name":"Philippe Vigneault","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04884784467895559,"gpt":0.3043260291810908,"spread":0.2554781845021352,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003352312,0.0001249835,0.0002133369,0.00001188426,0.0002016014,0.00001455983,0.0004218928,0.00007736155,0.00007489888],"category_scores_gemma":[0.0001590693,0.00008961388,0.00003143263,0.0001872391,0.00005277786,0.0001081152,0.0001861775,0.00009329178,0.00004771058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003835404,"about_ca_system_score_gemma":0.000007821017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004902063,"about_ca_topic_score_gemma":0.0001355115,"domain_scores_codex":[0.9988266,0.00006536775,0.0002886784,0.0003495937,0.0002965367,0.0001732497],"domain_scores_gemma":[0.9991257,0.000166911,0.0001914477,0.0003882766,0.00004934981,0.00007829703],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001173006,0.0003686947,0.07124353,0.00001821584,0.00003769114,6.408393e-7,0.0007501706,0.009390034,0.2222277,0.0001562668,0.6797141,0.01597559],"study_design_scores_gemma":[0.003603629,0.0002257796,0.1765373,0.00006100268,0.0002132836,0.0000272394,0.000299277,0.1221699,0.02807093,0.004535623,0.6633096,0.0009464779],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5708861,0.0002169084,0.42134,0.0003910418,0.0002344452,0.00171278,0.002116346,0.00008752539,0.003014933],"genre_scores_gemma":[0.9798184,0.00001803374,0.01898595,0.00008548085,0.00005184805,0.00003298812,0.0008225298,0.000009240352,0.0001754967],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4089324,"threshold_uncertainty_score":0.3654348,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2108085720","doi":"10.1111/j.1467-9868.2004.00437.x","title":"Penalized Triograms: Total Variation Regularization for Bivariate Smoothing","year":2003,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series B (Statistical Methodology)","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":129,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Univerzita Karlova v Praze; National Science Foundation","keywords":"Mathematics; Smoothing; Spline (mechanical); Affine transformation; Penalty method; Univariate; Regularization (linguistics); Bivariate analysis; Triangulation; Applied mathematics; Mathematical optimization; Algorithm; Computer science; Statistics; Geometry; Artificial intelligence; Multivariate statistics","authors":[{"name":"Roger Koenker","is_ca":false},{"name":"Ivan Mizera","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03709049989774942,"gpt":0.2939414294832984,"spread":0.2568509295855489,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004082395,0.0002781807,0.0005946271,0.00002600012,0.0005309802,0.0001102395,0.0003337646,0.0002266674,0.001169755],"category_scores_gemma":[0.01778154,0.0001993585,0.000312224,0.0003210457,0.0006105818,0.0001684885,0.000141215,0.0004839346,0.00001351332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002594237,"about_ca_system_score_gemma":0.00009771407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001231156,"about_ca_topic_score_gemma":0.0000100206,"domain_scores_codex":[0.9963405,0.001119862,0.00101112,0.00035404,0.0006220562,0.0005524421],"domain_scores_gemma":[0.9932362,0.005441072,0.0006776393,0.0002446856,0.0001446345,0.0002557611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006799974,0.0002445122,0.001205032,0.0001153729,0.0003526329,0.00002052896,0.001500251,0.009193905,0.002119278,0.9454381,0.0240298,0.01510063],"study_design_scores_gemma":[0.002670409,0.0008037462,0.04411956,0.00005004927,0.0006701117,0.0001627652,0.0004172776,0.03268689,0.0003954263,0.8924743,0.02501964,0.0005298375],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002373669,0.0000366277,0.9943249,0.0006964538,0.001214096,0.0004059629,0.0002116102,0.00002045962,0.0007161776],"genre_scores_gemma":[0.03792009,0.00001552799,0.960436,0.0005121641,0.000144081,0.00002107399,0.00001907772,0.00003656304,0.000895346],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05296377,"threshold_uncertainty_score":0.9997433,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2090405634","doi":"10.1080/136588100750022804","title":"Determination of grid size for digital terrain modelling in landscape investigations—exemplified by soil moisture distribution at a micro-scale","year":2000,"lang":"en","type":"article","venue":"International Journal of Geographical Information Systems","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":125,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"","keywords":"Terrain; Scale (ratio); Digital elevation model; Grid; Correlation coefficient; Interval (graph theory); Mathematics; Data set; Remote sensing; Geodesy; Soil science; Statistics; Geometry; Geography; Environmental science; Cartography","authors":[{"name":"Igor V. Florinsky","is_ca":true},{"name":"Galina A. Kuryakova","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.006503802828063325,"gpt":0.2158539737944652,"spread":0.2093501709664019,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004112505,0.000104417,0.0001768132,0.0001145679,0.00005560029,0.0001309663,0.0002279221,0.00009021073,0.00006732628],"category_scores_gemma":[0.0001174406,0.00009525361,0.0001031313,0.0001985278,0.00008395825,0.001039567,0.00003550503,0.0001115527,0.00001136177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000133803,"about_ca_system_score_gemma":0.00001627398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002285104,"about_ca_topic_score_gemma":0.00002677469,"domain_scores_codex":[0.9982491,0.00002679581,0.0009738457,0.00008508695,0.0005302978,0.0001349268],"domain_scores_gemma":[0.9989392,0.0001726111,0.0005637889,0.00007019245,0.0001750661,0.00007913946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001350036,0.0005636013,0.4221696,0.0002283975,0.000203195,0.000009061566,0.005794248,0.4712721,0.004653781,0.0009689552,0.02633304,0.06645397],"study_design_scores_gemma":[0.005348686,0.0003780251,0.06285953,0.0006054047,0.000054133,0.0002881267,0.001177449,0.7934154,0.001201853,0.003152334,0.1308963,0.0006227263],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8945386,0.00004255604,0.1027599,0.0003239253,0.0003455222,0.000242599,0.0008803144,0.000009013877,0.0008575401],"genre_scores_gemma":[0.9980604,0.00003963576,0.001137857,0.00007281788,0.00006903955,0.00001661174,0.0005297133,0.000004883477,0.00006905469],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3593101,"threshold_uncertainty_score":0.3884329,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2156892295","doi":"10.5194/gmd-5-819-2012","title":"Towards a public, standardized, diagnostic benchmarking system for land surface models","year":2012,"lang":"en","type":"article","venue":"Geoscientific model development","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":124,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; Biological and Environmental Research; Natural Sciences and Engineering Research Council of Canada; Oak Ridge National Laboratory; University of New South Wales; Microsoft Research; Canadian Foundation for Climate and Atmospheric Sciences; Natural Resources Canada; Université Laval; U.S. Department of Energy; National Science Foundation","keywords":"Benchmarking; A priori and a posteriori; Computer science; Protocol (science); Work (physics); Business; Engineering","authors":[{"name":"Gab Abramowitz","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03648892098034696,"gpt":0.2361041233209256,"spread":0.1996152023405786,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00194672,0.0002474512,0.0002472968,0.0000627937,0.0006623843,0.0002075251,0.0003156679,0.00007838173,0.0001405236],"category_scores_gemma":[0.0001160083,0.0002289637,0.00006675899,0.0002653991,0.00009883103,0.000452681,0.0003930246,0.00008427454,0.00009787455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000649164,"about_ca_system_score_gemma":0.0001548995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001478304,"about_ca_topic_score_gemma":0.00009791416,"domain_scores_codex":[0.9972254,0.00003614521,0.0004295443,0.000549635,0.0007501831,0.001009103],"domain_scores_gemma":[0.9989669,0.0001368527,0.0001324952,0.0003329535,0.00005687678,0.0003739539],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008247011,0.0005902892,0.05415165,0.0005893864,0.000154802,0.00001102284,0.01338722,0.684529,0.001464171,0.01571615,0.04773623,0.1815876],"study_design_scores_gemma":[0.000714814,0.00001494267,0.004366998,0.00007283628,0.00002947592,0.000009201176,0.0002186997,0.9165305,0.0004668091,0.001121106,0.0758651,0.0005895218],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1938616,0.0001022872,0.7977016,0.00006413741,0.001297953,0.0006285403,0.0001719656,0.00009615828,0.006075726],"genre_scores_gemma":[0.8166806,0.000008701643,0.1816079,0.00005237561,0.0000458126,0.0001550248,0.0001206658,0.0000249841,0.001304054],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6228189,"threshold_uncertainty_score":0.9336867,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1611105082","doi":"10.1111/2041-210x.12407","title":"Generating spatially constrained null models for irregularly spaced data using <scp>M</scp>oran spectral randomization methods","year":2015,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":124,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Autocorrelation; Mathematics; Statistics; Type I and type II errors; Spatial analysis; Algorithm; Restricted randomization; Statistical hypothesis testing; Factorial; Randomization","authors":[{"name":"Helene H. Wagner","is_ca":true},{"name":"Stéphane Dray","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0946685942089314,"gpt":0.376660171269256,"spread":0.2819915770603246,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006385471,0.0001487605,0.0003025582,0.0000843712,0.0001854565,0.00003739933,0.0001668882,0.000147713,0.00001125878],"category_scores_gemma":[0.003459485,0.0001534945,0.00002645144,0.0001911726,0.0002763294,0.0003666813,0.000208079,0.0001274427,0.000001480431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002185384,"about_ca_system_score_gemma":0.00007761019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006727239,"about_ca_topic_score_gemma":0.001275501,"domain_scores_codex":[0.9975937,0.001160708,0.0003482818,0.0004521114,0.00009709143,0.0003480982],"domain_scores_gemma":[0.9982648,0.001186919,0.0001730307,0.0002453786,0.00003017512,0.00009971503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002003713,0.0001157612,0.03501965,0.00004008396,0.00005855685,0.000007581676,0.001857795,0.8458331,0.05465289,0.009445626,0.0006280195,0.05214062],"study_design_scores_gemma":[0.002682089,0.00006885506,0.006925196,0.000007428941,0.00004986257,0.00001911393,0.0003437392,0.9332486,0.0003404794,0.05600198,0.0002273719,0.00008524061],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1230284,0.0001109895,0.8752629,0.00007360816,0.0004350402,0.0004583947,0.00002089707,0.00002312898,0.0005866705],"genre_scores_gemma":[0.137401,0.000009671106,0.8622839,0.00006684211,0.00007369863,0.00002497412,0.00006372295,0.00001285727,0.00006337246],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0874156,"threshold_uncertainty_score":0.6259325,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3097245740","doi":"10.1016/j.geoderma.2020.114793","title":"Improving the spatial prediction of soil salinity in arid regions using wavelet transformation and support vector regression models","year":2020,"lang":"en","type":"article","venue":"Geoderma","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":123,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Dalhousie University","funders":"Deutsche Forschungsgemeinschaft; Alexander von Humboldt-Stiftung","keywords":"Soil salinity; Environmental science; Digital soil mapping; Covariate; Salinity; Soil science; Topsoil; Soil map; Support vector machine; Spatial variability; Digital elevation model; Hydrology (agriculture); Statistics; Mathematics; Soil water; Geology; Remote sensing; Computer science; Machine learning","authors":[{"name":"Ruhollah Taghizadeh‐Mehrjardi","is_ca":false},{"name":"Karsten Schmidt","is_ca":false},{"name":"Norair Toomanian","is_ca":false},{"name":"Brandon Heung","is_ca":true},{"name":"Thorsten Behrens","is_ca":false},{"name":"Amirhosein Mosavi","is_ca":false},{"name":"Shahab S. Band","is_ca":false},{"name":"Alireza Amirian‐Chakan","is_ca":false},{"name":"Aboalhasan Fathabadi","is_ca":false},{"name":"Thomas Scholten","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03286731194419507,"gpt":0.2294137791944478,"spread":0.1965464672502527,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001462741,0.00006490923,0.00008264642,0.00001473948,0.00009314231,0.0000122547,0.00005641911,0.00003852478,0.00003873755],"category_scores_gemma":[0.00002708531,0.00004953106,0.00001750565,0.00007868733,0.00006579269,0.0001972367,0.00005406862,0.00009481221,0.000002354204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002809258,"about_ca_system_score_gemma":0.0000140968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002898688,"about_ca_topic_score_gemma":0.0002764156,"domain_scores_codex":[0.9993765,0.00003414105,0.0001963893,0.0001262588,0.0001496003,0.0001170854],"domain_scores_gemma":[0.9997661,0.00002668935,0.0000799401,0.00007718727,0.0000061102,0.00004398319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003808076,0.0002285986,0.06444606,0.0005251652,0.00004185407,0.00003506185,0.08412586,0.2757657,0.2850986,0.002113828,0.001558283,0.2856802],"study_design_scores_gemma":[0.0002710659,0.00003470036,0.0425377,0.00001441554,0.00001099398,0.000005608916,0.0002592422,0.954206,0.00178132,0.0007807893,0.0000459354,0.00005215194],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8452347,0.000008362378,0.1534732,0.0005985408,0.00005074462,0.0001591542,0.00003801546,0.000013457,0.0004238036],"genre_scores_gemma":[0.9992126,0.00002138217,0.0005605003,0.0001469337,0.00002618642,0.000003838467,0.00001967265,0.000005032675,0.000003801919],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6784404,"threshold_uncertainty_score":0.4381969,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2115543162","doi":"10.4141/cjss10029","title":"Predicting soil organic carbon and total nitrogen using mid- and near-infrared spectra for Brookston clay loam soil in Southwestern Ontario, Canada","year":2011,"lang":"en","type":"article","venue":"Canadian Journal of Soil Science","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":122,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true},"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada; Chinese Academy of Sciences; University of Otago","keywords":"Loam; Soil carbon; Soil water; Total organic carbon; Soil test; Environmental science; Soil science; Tillage; Chemistry; Environmental chemistry; Agronomy","authors":[{"name":"Hongtu Xie","is_ca":false},{"name":"X.M. Yang","is_ca":true},{"name":"Colin Drury","is_ca":true},{"name":"Jing Yang","is_ca":true},{"name":"Xu Dong Zhang","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01373083475815785,"gpt":0.1873061842896508,"spread":0.173575349531493,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000563503,0.0001457693,0.0001929068,0.0001190194,0.0003484346,0.0001350846,0.0002522616,0.00004778188,0.0000861946],"category_scores_gemma":[0.0001336299,0.0001462415,0.00002166898,0.0002830829,0.0005787708,0.0002912831,0.00006312977,0.0002020002,4.197914e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001152809,"about_ca_system_score_gemma":0.004140621,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.994554,"about_ca_topic_score_gemma":0.9996403,"domain_scores_codex":[0.9984803,0.00001800164,0.0003269262,0.0002772201,0.0003015576,0.0005960334],"domain_scores_gemma":[0.998809,0.00003729925,0.00019507,0.000120461,0.000043271,0.0007949323],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009651543,0.000004790648,0.989688,0.000008465803,0.000005845885,0.00008945958,0.005221553,0.0007343963,0.003394713,0.00000702698,0.00002457283,0.0008115042],"study_design_scores_gemma":[0.0006298749,0.0001393122,0.9766076,0.00009810916,0.00003176926,0.0004900112,0.001215799,0.01636071,0.003037018,0.00103133,0.0000662736,0.0002921479],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979191,0.00008052977,0.00005584583,0.00003409184,0.0003004425,0.0001063781,0.00001649475,0.00000248835,0.001484593],"genre_scores_gemma":[0.9986773,0.000002778825,0.001098407,0.0000896787,0.00003987629,0.000001175697,5.275949e-7,0.00001205011,0.00007824826],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01562631,"threshold_uncertainty_score":0.7345284,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3153963714","doi":"10.1016/j.geoderma.2021.115108","title":"Enhancing the accuracy of machine learning models using the super learner technique in digital soil mapping","year":2021,"lang":"en","type":"article","venue":"Geoderma","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":120,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Dalhousie University","funders":"University of Maragheh; Deutsche Forschungsgemeinschaft; Alexander von Humboldt-Stiftung","keywords":"Digital soil mapping; Computer science; Covariate; Range (aeronautics); Feature (linguistics); Machine learning; Variety (cybernetics); Base (topology); Soil map; Soil science; Artificial intelligence; Data mining; Environmental science; Mathematics; Soil water; Engineering","authors":[{"name":"Ruhollah Taghizadeh‐Mehrjardi","is_ca":false},{"name":"Nikou Hamzehpour","is_ca":false},{"name":"Brandon Heung","is_ca":true},{"name":"Maryam Ghebleh Goydaragh","is_ca":false},{"name":"Karsten Schmidt","is_ca":false},{"name":"Thomas Scholten","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02559423734149852,"gpt":0.2374219974620731,"spread":0.2118277601205746,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003887707,0.0001135709,0.000132292,0.00002549236,0.0002125739,0.00007346122,0.0002078854,0.00004478524,0.0001907983],"category_scores_gemma":[0.0002844932,0.00007556646,0.0000515515,0.0003115733,0.0001211264,0.0002755755,0.0004315439,0.000313705,0.00001184339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005553405,"about_ca_system_score_gemma":0.00003036452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001242681,"about_ca_topic_score_gemma":0.0004110222,"domain_scores_codex":[0.9989402,0.00006866,0.0002685328,0.0002136016,0.0002326078,0.0002764227],"domain_scores_gemma":[0.9993444,0.0002761038,0.00009056884,0.0002433346,0.00001712508,0.00002846932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008037707,0.00006410822,0.0503597,0.00004012561,0.00002331884,0.00005797999,0.006513023,0.7241175,0.1996336,0.000580057,0.0000765669,0.01852597],"study_design_scores_gemma":[0.0003008536,0.00001407473,0.007756732,0.0001455473,0.00001552108,0.0001280681,0.004122785,0.9415969,0.0352318,0.00731668,0.003057449,0.00031358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8587143,0.0001848476,0.1361665,0.0003442524,0.00004893636,0.0001774991,0.000007473166,0.00002163239,0.004334589],"genre_scores_gemma":[0.9979597,0.00003025855,0.001453824,0.0001831646,0.00002047181,0.00001370066,0.000008472033,0.00001468055,0.000315698],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2174795,"threshold_uncertainty_score":0.3081511,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2004526006","doi":"10.2136/sssaj2005.0214","title":"Probability Distribution and Spatial Dependence of Nitrous Oxide Emission","year":2006,"lang":"en","type":"article","venue":"Soil Science Society of America Journal","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":119,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Saskatchewan","funders":"Agriculture and Agri-Food Canada","keywords":"Variogram; Spatial distribution; Probability distribution; Environmental science; Mathematics; Flux (metallurgy); Atmospheric sciences; Statistics; Soil science; Kriging; Geology; Chemistry","authors":[{"name":"Thomas Yates","is_ca":true},{"name":"Bingcheng Si","is_ca":true},{"name":"R. Farrell","is_ca":true},{"name":"D.J. Pennock","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.008098884209047417,"gpt":0.2230648825930122,"spread":0.2149659983839648,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008005,0.00008472631,0.0001436464,0.0000116304,0.0003542099,0.00003285876,0.0002305544,0.00003171643,0.00005462946],"category_scores_gemma":[0.0001374901,0.00007078015,0.00007479979,0.000397185,0.002487219,0.0002385429,0.0001735344,0.0001457592,0.00000226788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001474722,"about_ca_system_score_gemma":0.00009479569,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009628274,"about_ca_topic_score_gemma":0.00005431957,"domain_scores_codex":[0.9985027,0.00002767843,0.0003035793,0.000213948,0.0006863691,0.0002656843],"domain_scores_gemma":[0.9993011,0.00004886709,0.0003499793,0.0001177782,0.00006432157,0.0001179867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002223641,0.0002001174,0.5936095,0.00003468182,0.000007398484,0.000001972255,0.0007439394,0.003582064,0.2774009,0.00007199359,0.004093702,0.1202315],"study_design_scores_gemma":[0.0003145949,0.0001659386,0.9397362,0.00004640504,0.000017164,0.00006692242,0.0007385984,0.02692536,0.01791719,0.01298612,0.0009030111,0.000182464],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9287654,0.00002583494,0.07036015,0.0001716905,0.00004736352,0.00005970443,0.00001264986,0.000006087616,0.000551116],"genre_scores_gemma":[0.9821458,0.00006660757,0.01770226,0.00003283312,0.0000225503,9.143155e-7,0.000002003768,0.000002729361,0.00002424707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3461268,"threshold_uncertainty_score":0.9969667,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2939636013","doi":"10.1016/j.geoderma.2019.04.003","title":"Estimating forest soil organic carbon content using vis-NIR spectroscopy: Implications for large-scale soil carbon spectroscopic assessment","year":2019,"lang":"en","type":"article","venue":"Geoderma","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":117,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Soil carbon; Environmental science; Partial least squares regression; Soil science; Soil organic matter; Soil test; Remote sensing; Scale (ratio); Total organic carbon; Soil water; Mathematics; Chemistry; Environmental chemistry; Geology; Statistics; Geography; Cartography","authors":[{"name":"Shangshi Liu","is_ca":false},{"name":"Haihua Shen","is_ca":false},{"name":"Songchao Chen","is_ca":false},{"name":"Xia Zhao","is_ca":false},{"name":"Asim Biswas","is_ca":true},{"name":"Xiaolin Jia","is_ca":false},{"name":"Zhou Shi","is_ca":false},{"name":"Jingyun Fang","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01966536862022379,"gpt":0.2769495930257198,"spread":0.257284224405496,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002485883,0.0002579007,0.0003042085,0.00004837131,0.0002585144,0.00008600987,0.0002484043,0.00008593929,0.000233989],"category_scores_gemma":[0.00003410119,0.0002649393,0.0000803639,0.0001968004,0.00005268347,0.0001007555,0.0002378102,0.0001774823,0.00004404162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005385648,"about_ca_system_score_gemma":0.00007791637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001773959,"about_ca_topic_score_gemma":0.002601832,"domain_scores_codex":[0.9980202,0.0000323231,0.0003736952,0.0005700505,0.0002514547,0.0007522597],"domain_scores_gemma":[0.9990313,0.00008734569,0.0002061109,0.0005017912,0.00002983268,0.0001435992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008500461,0.0001197899,0.6746234,0.00006207687,0.00002918559,0.000001942373,0.0002998669,0.01559487,0.3082125,0.0006105138,0.00009336507,0.0003439388],"study_design_scores_gemma":[0.0007696635,0.00009510871,0.3112547,0.00003899995,0.00005379123,0.000009582598,0.0001790298,0.6808179,0.004089681,0.002265924,0.0001265374,0.0002991187],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9271894,0.00002924066,0.06399105,0.0003681458,0.0004759686,0.0007653408,0.00003859051,0.0000796266,0.007062633],"genre_scores_gemma":[0.9596688,0.00000711594,0.03946822,0.0002171409,0.0001436883,0.00008129555,0.00005603753,0.00005055464,0.0003071814],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.665223,"threshold_uncertainty_score":0.9999803,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1990669485","doi":"10.1016/j.jenvrad.2007.05.008","title":"Assessment of spatial distribution of fallout radionuclides through geostatistics concept","year":2007,"lang":"en","type":"article","venue":"Journal of Environmental Radioactivity","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":117,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Ministry of Agriculture, Fisheries and Food","funders":"International Atomic Energy Agency","keywords":"Geostatistics; Kriging; Variogram; Inverse distance weighting; Environmental science; Spatial analysis; Radionuclide; Soil science; Multivariate interpolation; Interpolation (computer graphics); Spatial variability; Hydrology (agriculture); Geology; Statistics; Mathematics; Computer science","authors":[{"name":"Lionel Mabit","is_ca":false},{"name":"Claude Bernard","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.009118153799268867,"gpt":0.2634128969885196,"spread":0.2542947431892507,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000795034,0.0001641723,0.0004074148,0.0000318175,0.00007001763,0.000007627215,0.0001932244,0.00007640893,0.0005083873],"category_scores_gemma":[0.0001005144,0.0001520312,0.0001481435,0.00008796131,0.0005495342,0.0002863499,0.0001049557,0.0002373835,0.000003281003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005220961,"about_ca_system_score_gemma":0.00002461246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004047711,"about_ca_topic_score_gemma":0.00003011328,"domain_scores_codex":[0.9979854,0.0000820557,0.0007720399,0.0001653381,0.0007474553,0.0002476627],"domain_scores_gemma":[0.9982196,0.0003412399,0.001127652,0.0001814125,0.00001085495,0.0001192312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002198162,0.001751179,0.6508083,0.00004221156,0.0002197695,0.0001110361,0.0009694924,0.004873915,0.2373622,0.001301856,0.0007234384,0.1016168],"study_design_scores_gemma":[0.0007642558,0.0004496243,0.9784259,0.00002847582,0.00007982915,0.00006834372,0.0002635306,0.0006389939,0.01712084,0.0005644184,0.001453734,0.0001421124],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6692407,0.00005402794,0.3294081,0.00001752939,0.0002001004,0.00009566117,0.0002434463,0.000002344263,0.0007380781],"genre_scores_gemma":[0.984525,0.0001288677,0.01519748,0.00002102807,0.00006783447,5.660327e-7,0.0000249021,0.00001228596,0.00002204501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3276175,"threshold_uncertainty_score":0.6199652,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2141363828","doi":"10.1080/13658810410001701987","title":"The choice of window size in approximating topographic surfaces from Digital Elevation Models","year":2004,"lang":"en","type":"article","venue":"International Journal of Geographical Information Systems","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":115,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of British Columbia","funders":"R. Howard Webster Foundation","keywords":"Elevation (ballistics); Digital elevation model; Curvature; Scale (ratio); Mathematics; Autocorrelation; Geodesy; Geometry; Statistics; Geology; Geography; Remote sensing; Cartography","authors":[{"name":"Marco Albani","is_ca":true},{"name":"Brian Klinkenberg","is_ca":true},{"name":"David Andison","is_ca":true},{"name":"J. P. Kimmins","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01087469446257724,"gpt":0.2323395681285492,"spread":0.2214648736659719,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006111459,0.00009010201,0.0001564245,0.000148354,0.00006087992,0.0002614118,0.0004010229,0.00005686291,0.00001018472],"category_scores_gemma":[0.0004592359,0.00006533788,0.00009106103,0.0003282868,0.0001206275,0.001982247,0.00007167456,0.0001730953,0.000006746425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008101311,"about_ca_system_score_gemma":0.00002267112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001773562,"about_ca_topic_score_gemma":0.00007627071,"domain_scores_codex":[0.9977625,0.00003058435,0.001118599,0.00006371064,0.0008973624,0.0001272198],"domain_scores_gemma":[0.9982171,0.0004898842,0.0009481824,0.00008921565,0.0002026779,0.0000529279],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001166641,0.0001179973,0.3172055,0.00001859191,0.0001750956,0.000004879738,0.001983229,0.6479887,0.0006311892,0.01637879,0.00006477367,0.01531461],"study_design_scores_gemma":[0.003626886,0.0001909831,0.8254644,0.0005939374,0.00002649669,0.00006299226,0.003880189,0.09902596,0.0001678955,0.06102001,0.005572357,0.0003679153],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9760775,0.00007927324,0.02111494,0.0003885968,0.0005669306,0.0001393591,0.00003971639,0.000007462652,0.001586218],"genre_scores_gemma":[0.9991459,0.00006602037,0.0006574061,0.00005057783,0.00005631161,0.000004462952,0.00001222655,0.000003486078,0.000003633994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5489628,"threshold_uncertainty_score":0.2681108,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3112145214","doi":"10.3390/rs12244118","title":"Integrating Remote Sensing and Landscape Characteristics to Estimate Soil Salinity Using Machine Learning Methods: A Case Study from Southern Xinjiang, China","year":2020,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":108,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"National Key Research and Development Program of China","keywords":"Soil salinity; Environmental science; Salinity; Arid; Arable land; Dryland salinity; Vegetation (pathology); Soil science; Remote sensing; Hydrology (agriculture); Soil water; Soil organic matter; Geography; Soil biodiversity; Geology; Agriculture","authors":[{"name":"Nan Wang","is_ca":false},{"name":"Jie Xue","is_ca":false},{"name":"Jie Peng","is_ca":false},{"name":"Asim Biswas","is_ca":true},{"name":"Yong He","is_ca":false},{"name":"Zhou Shi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03063319654324518,"gpt":0.3146456152316628,"spread":0.2840124186884176,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008087001,0.0003744886,0.000514495,0.00006092697,0.0006483945,0.0002500831,0.00009425097,0.0000910098,0.0000300641],"category_scores_gemma":[0.001387178,0.0003694966,0.00006053956,0.0003602073,0.00007031066,0.00009308595,0.0005339845,0.0005773242,0.00003791318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009709528,"about_ca_system_score_gemma":0.00002249137,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06145681,"about_ca_topic_score_gemma":0.002711434,"domain_scores_codex":[0.9974572,0.0005228333,0.000517734,0.000745111,0.0002825136,0.0004745799],"domain_scores_gemma":[0.9987253,0.0003121851,0.0002810413,0.0002706348,0.0000290489,0.0003818059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000580374,0.00001047428,0.003855299,0.00002886211,0.00005251656,0.003299161,0.04032882,0.004716277,0.04075008,2.391065e-7,0.000004972503,0.9068953],"study_design_scores_gemma":[0.0003779398,0.0001005415,0.00135329,0.0001506549,0.0001215141,0.000802247,0.009523213,0.9866486,0.0002794323,0.0001052342,0.0001178915,0.0004194088],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5983308,0.00003001189,0.4010051,0.000103489,0.00008938875,0.0002015827,0.0000158169,0.00009569339,0.0001281221],"genre_scores_gemma":[0.578751,0.000003220482,0.4208683,0.0001887,0.000117605,4.742574e-9,0.000009762734,0.00004748174,0.00001389418],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9819323,"threshold_uncertainty_score":0.9998757,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1998398443","doi":"10.1007/s11004-008-9178-0","title":"Block Simulation of Multiple Correlated Variables","year":2008,"lang":"en","type":"article","venue":"Mathematical Geosciences","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":108,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Block (permutation group theory); Computer science; Multivariate statistics; Algorithm; Multivariate normal distribution; Block size; Kriging; Gaussian; Multivariate random variable; Mathematical optimization; Statistics; Random variable; Mathematics; Machine learning; Geometry","authors":[{"name":"Alexandre Boucher","is_ca":false},{"name":"Roussos Dimitrakopoulos","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02392817042549622,"gpt":0.241100842954073,"spread":0.2171726725285768,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002290145,0.00007448945,0.000129843,0.00002383435,0.0001511513,0.00000947383,0.0001730341,0.00003596859,0.001019645],"category_scores_gemma":[0.0005889639,0.00005735001,0.0000281738,0.0003066106,0.0004729036,0.00009700355,0.00009588643,0.00004469322,0.0002512843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001487411,"about_ca_system_score_gemma":0.00001005685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001358713,"about_ca_topic_score_gemma":0.000007233202,"domain_scores_codex":[0.9990354,0.00001952921,0.0002353197,0.0001732336,0.0003562011,0.0001803305],"domain_scores_gemma":[0.9993239,0.0003813637,0.00008436149,0.0001318562,0.00001221217,0.00006630919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004036346,0.001350485,0.2267878,0.0001484098,0.00003313068,0.0000486821,0.008766482,0.7103623,0.02040753,0.01864471,0.00259339,0.01081671],"study_design_scores_gemma":[0.0001562213,0.00005042702,0.02972878,0.00002001661,0.000007608546,0.00001431052,0.00009889631,0.9517972,0.0004981975,0.0165631,0.0009484703,0.0001167328],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9043096,0.000008814633,0.07266135,0.00003390921,0.00009873872,0.0001334234,0.000005478164,0.00003579331,0.02271291],"genre_scores_gemma":[0.9866028,0.000003646496,0.01257642,0.00003005764,0.000007287548,0.000003813876,0.000001004298,0.000003652011,0.0007712619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.241435,"threshold_uncertainty_score":0.9998935,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2912648180","doi":"10.1016/j.geoderma.2019.01.006","title":"Simultaneous measurement of multiple soil properties through proximal sensor data fusion: A case study","year":2019,"lang":"en","type":"article","venue":"Geoderma","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":106,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph; Agriculture and Agri-Food Canada; McGill University; Nutrasource","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Agriculture, Food and Rural Affairs","keywords":"Environmental science; Soil science; Soil water; Remote sensing; Sensor fusion; Soil test; Soil organic matter; Computer science; Geology; Machine learning","authors":[{"name":"Wenjun Ji","is_ca":true},{"name":"Viacheslav I. Adamchuk","is_ca":true},{"name":"Songchao Chen","is_ca":false},{"name":"Ahmad Suhaizi Mat Su","is_ca":true},{"name":"Ashraf A. Ismail","is_ca":true},{"name":"Qianjun Gan","is_ca":true},{"name":"Zhou Shi","is_ca":false},{"name":"Asim Biswas","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06518803768647176,"gpt":0.2552467782234076,"spread":0.1900587405369358,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003145807,0.0001409456,0.0001831424,0.00001261294,0.0001049894,0.00002289809,0.0002934806,0.00003299797,0.0003578281],"category_scores_gemma":[0.0001774853,0.0001118425,0.00002186475,0.00009612554,0.00007508448,0.0001599021,0.0007597947,0.00008593798,0.0002520947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005385343,"about_ca_system_score_gemma":0.00002189496,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009504184,"about_ca_topic_score_gemma":0.002394994,"domain_scores_codex":[0.9984218,0.00006119509,0.0002597113,0.0004171316,0.0005840277,0.0002561649],"domain_scores_gemma":[0.9989812,0.00005857212,0.00009492735,0.0007785508,0.00003623188,0.00005047362],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004272315,0.004303609,0.6738798,0.0005004346,0.0002990111,0.008774181,0.04498536,0.08852798,0.1148476,0.00001189992,0.004014556,0.05942833],"study_design_scores_gemma":[0.005201237,0.00114638,0.01771044,0.0001542269,0.0001890577,0.002093674,0.04310254,0.9092253,0.007376247,0.00009326153,0.01256635,0.001141333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975752,0.00005346241,0.0003740503,0.00005018254,0.0001272826,0.0008706602,0.00005056765,0.00003046785,0.0008681369],"genre_scores_gemma":[0.9981691,0.000004380777,0.001383612,0.0000691274,0.00002373363,0.00001524917,0.000009926983,0.00001421989,0.0003106605],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8206973,"threshold_uncertainty_score":0.9970916,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1998420573","doi":"10.4141/s01-054","title":"Determination of soil organic carbon and nitrogen at the field level using near-infrared spectroscopy","year":2002,"lang":"en","type":"article","venue":"Canadian Journal of Soil Science","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":105,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Partial least squares regression; Total organic carbon; Chemistry; Nitrogen; Soil test; Soil carbon; Principal component analysis; Chemical composition; Linear regression; Analytical Chemistry (journal); Soil science; Environmental chemistry; Soil water; Environmental science; Mathematics","authors":[{"name":"P. D. Martin","is_ca":false},{"name":"D. F. Malley","is_ca":false},{"name":"G. Manning","is_ca":false},{"name":"Lourdes C. Fuller","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02028960214753552,"gpt":0.2266312772880426,"spread":0.2063416751405071,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004092635,0.0000675588,0.00009307221,0.00006579917,0.0003924301,0.00007380168,0.0002761649,0.00002640481,0.0004643789],"category_scores_gemma":[0.0003069296,0.00005307704,0.00002161966,0.0003652385,0.0007144325,0.0001683246,0.00005460679,0.00009585673,0.000004502565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003054072,"about_ca_system_score_gemma":0.0002092211,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02281918,"about_ca_topic_score_gemma":0.07080448,"domain_scores_codex":[0.9991322,0.00001854544,0.0001910259,0.0001170977,0.0002818694,0.000259287],"domain_scores_gemma":[0.999318,0.00006649049,0.0001762982,0.0001214191,0.00003873944,0.0002790361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001598353,0.0000320133,0.68582,0.00002844882,0.00001903982,0.000204192,0.009955718,0.003061873,0.2392266,0.0001190281,0.003434873,0.05808217],"study_design_scores_gemma":[0.0009150358,0.0005455372,0.3795491,0.000174226,0.00009991381,0.00102209,0.001101106,0.4594609,0.1483669,0.006340556,0.001817403,0.0006072904],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956055,0.0001438623,0.000405711,0.0003439898,0.0001440479,0.00003932169,0.00000458113,0.000001106016,0.003311903],"genre_scores_gemma":[0.9975967,0.00001874636,0.00202471,0.00020117,0.00002410993,2.372711e-7,8.845494e-8,0.000004409366,0.0001298576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.456399,"threshold_uncertainty_score":0.9836879,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2506401077","doi":"10.1007/978-1-4020-3610-1","title":"Geostatistics Banff 2004","year":2005,"lang":"en","type":"book","venue":"Quantitative geology and geostatistics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":105,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Geostatistics; Beauty; Geography; Ideal (ethics); Physical geography; Geology; Mathematics; Statistics; Art; Aesthetics; Political science; Spatial variability","authors":[{"name":"Oy Leuangthong","is_ca":true},{"name":"Clayton V. Deutsch","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01560530058550759,"gpt":0.2587210415367155,"spread":0.2431157409512079,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004336973,0.0007675882,0.000871221,0.0001586136,0.0004948803,0.00006962979,0.0003571757,0.000654283,0.004510301],"category_scores_gemma":[0.0007700471,0.0008032653,0.00008877697,0.0001408632,0.002293478,0.0001229313,0.0004978111,0.0009185359,0.003606028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002666233,"about_ca_system_score_gemma":0.000194384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003649927,"about_ca_topic_score_gemma":0.001273799,"domain_scores_codex":[0.996641,0.0001576365,0.0007888279,0.001052686,0.0004896268,0.0008702316],"domain_scores_gemma":[0.9967119,0.001822546,0.0005644783,0.0004907346,0.00007828831,0.0003321253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006732073,0.00005958256,0.001037792,0.00008969113,0.0001532736,0.0002994556,0.0006737801,0.00031975,0.000003914692,0.4842499,0.4760986,0.03694693],"study_design_scores_gemma":[0.0006796113,0.0004742804,0.007012753,0.0000755628,0.0002441948,0.00009460887,0.0001031606,0.004908847,0.000001281502,0.2553137,0.7301091,0.0009829232],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0005071776,0.004333943,0.2090101,0.0008034467,0.001452378,0.001074136,0.004284439,0.0001990278,0.7783353],"genre_scores_gemma":[0.0006423577,0.001995146,0.1745138,0.001706819,0.0002864641,0.00004634984,0.002190283,0.0001461632,0.8184726],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2540105,"threshold_uncertainty_score":0.9994418,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4213448449","doi":"10.1002/ecs2.3940","title":"A case for beta regression in the natural sciences","year":2022,"lang":"en","type":"article","venue":"Ecosphere","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":104,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Regression analysis; Linear regression; Statistics; Bounded function; Regression; Transformation (genetics); Mathematics; Compositional data; BETA (programming language); Regression diagnostic; Econometrics; Computer science; Polynomial regression; Biology; Mathematical analysis","authors":[{"name":"Emilie A. Geissinger","is_ca":true},{"name":"Celyn L. L. Khoo","is_ca":true},{"name":"Isabella C. Richmond","is_ca":true},{"name":"Sally J. M. Faulkner","is_ca":true},{"name":"David C. Schneider","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0191732277901514,"gpt":0.2620272619001843,"spread":0.2428540341100329,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003866902,0.00003938426,0.00003711502,0.00000439449,0.0004993575,0.00002225764,0.0001822909,0.000006491399,0.001797894],"category_scores_gemma":[0.0000227389,0.00002536857,0.00001739649,0.0001681059,0.00005320973,0.00004374022,0.0001381134,0.00007752307,0.00002781219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004059296,"about_ca_system_score_gemma":0.000006709658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004636493,"about_ca_topic_score_gemma":0.0008712977,"domain_scores_codex":[0.9995,0.0000359468,0.0000631736,0.0001307093,0.0001399755,0.0001301898],"domain_scores_gemma":[0.9997809,0.0001010683,0.0000264659,0.0000787982,0.000001037649,0.00001172927],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003450187,0.0001654449,0.01423831,0.00001695993,0.000005619974,0.001350382,0.006181668,0.01686861,0.00035062,0.008755484,0.8117354,0.140297],"study_design_scores_gemma":[0.001553077,0.000616055,0.05472153,0.00002450193,0.00001835074,0.002732954,0.02883596,0.1704646,0.0001545564,0.0247474,0.7155029,0.0006281288],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9680258,0.0001406901,0.00009558028,0.0009035717,0.0002165724,0.0002171031,0.00001454841,0.000008050894,0.0303781],"genre_scores_gemma":[0.9973413,0.000001548415,0.001566213,0.000398585,0.00001396361,0.00006346595,0.000002756597,0.000002513956,0.0006096778],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.153596,"threshold_uncertainty_score":0.9991146,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1967069051","doi":"10.1007/s11004-013-9497-7","title":"Projection Pursuit Multivariate Transform","year":2013,"lang":"en","type":"article","venue":"Mathematical Geosciences","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":103,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Projection pursuit; Multivariate statistics; Gaussian; Projection (relational algebra); Multivariate normal distribution; Context (archaeology); Geostatistics; Computer science; Mathematics; Algorithm; Artificial intelligence; Data mining; Statistics; Geography; Spatial variability","authors":[{"name":"Ryan M. Barnett","is_ca":true},{"name":"John G. Manchuk","is_ca":true},{"name":"Clayton V. Deutsch","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01704581197286067,"gpt":0.247180140883342,"spread":0.2301343289104813,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003052126,0.00009624547,0.000103813,0.00002422167,0.0001763269,0.0001346533,0.0002459346,0.00003469974,0.008577373],"category_scores_gemma":[0.0001245545,0.00006716498,0.00003322527,0.0002608333,0.0002716661,0.000302751,0.00007458845,0.00006418482,0.004386239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003162768,"about_ca_system_score_gemma":0.000006989721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001280147,"about_ca_topic_score_gemma":0.00003908641,"domain_scores_codex":[0.9988533,0.00001682299,0.0001832837,0.0002386427,0.0004054167,0.0003025912],"domain_scores_gemma":[0.9996535,0.00006999284,0.00003910731,0.0001227693,0.000008279003,0.0001063351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000008950598,0.0007940606,0.006227525,0.0001286464,0.00002110578,0.000009946684,0.006066804,0.0001356006,0.02940739,0.07217589,0.02057947,0.8644446],"study_design_scores_gemma":[0.0004241213,0.0002283374,0.1120482,0.00005045924,0.00002256254,0.00003514909,0.001354268,0.3316443,0.00115384,0.5290839,0.02335638,0.0005985484],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3280351,0.000009409669,0.2919751,0.002365677,0.0003910255,0.001170699,0.000005469978,0.0001925337,0.3758551],"genre_scores_gemma":[0.9350221,0.000003524206,0.0580069,0.000253373,0.00003132676,0.0001475841,0.000001256461,0.000008814448,0.006525132],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8638461,"threshold_uncertainty_score":0.996389,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}