{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":137,"total_is_capped":false,"direct_labels_cover":1,"predictions_cover":137,"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":"5c3543d363f9","filters":{"topic":"Statistical Methods and Applications"}},"results":[{"id":"W1988619277","doi":"10.1890/07-0986.1","title":"FORWARD SELECTION OF EXPLANATORY VARIABLES","year":2008,"lang":"en","type":"article","venue":"Ecology","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":2123,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Univariate; Multivariate statistics; Selection (genetic algorithm); Variance (accounting); Variable (mathematics); Statistics; Econometrics; Feature selection; Model selection; Computer science; Mathematics; Artificial intelligence; Economics","authors":[{"name":"F. Guillaume Blanchet","is_ca":true},{"name":"Pierre Legendre","is_ca":true},{"name":"Daniel Borcard","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07268296521155287,"gpt":0.364527027550163,"spread":0.2918440623386102,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02403266,0.002645163,0.002541402,0.003338022,0.001476941,0.002385395,0.002588309,0.001322759,0.005607382],"category_scores_gemma":[0.0523564,0.0008212258,0.003715879,0.003306777,0.001308281,0.002398615,0.00377118,0.003043251,0.002213106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000673782,"about_ca_system_score_gemma":0.003091168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002405166,"about_ca_topic_score_gemma":0.002755374,"domain_scores_codex":[0.9842616,0.0111656,0.0004995962,0.001669089,0.001990756,0.0004132482],"domain_scores_gemma":[0.9727638,0.01947246,0.0012267,0.002955463,0.003277248,0.0003044326],"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":[0.0007091601,0.0004441833,0.02883219,0.001177423,0.001954278,0.001049433,0.002059994,0.06612416,0.008469501,0.09091319,0.01043769,0.7878288],"study_design_scores_gemma":[0.0004377748,0.001265896,0.01447878,0.00082489,0.001185818,0.001081128,0.0006359756,0.5857958,0.01569257,0.323659,0.05452049,0.0004218746],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0087881,0.0003730084,0.9878821,0.000378657,0.0003092549,0.0001783913,0.0002448041,0.0005552675,0.001290272],"genre_scores_gemma":[0.1471333,0.0009328353,0.8426843,0.0006430327,0.0004951507,0.00117986,0.001274878,0.0004312883,0.005225266],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02403266,"threshold_uncertainty_score":0.1270984,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2098405376","doi":"10.1007/s11336-010-9200-6","title":"OpenMx: An Open Source Extended Structural Equation Modeling Framework","year":2011,"lang":"en","type":"article","venue":"Psychometrika","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":1202,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"National Institute on Drug Abuse; National Institutes of Health","keywords":"Scripting language; Structural equation modeling; Computer science; Interface (matter); Open source; Programming language; Software; Software engineering; User interface; Statistical model; Theoretical computer science; Computational science; Operating system; Machine learning","authors":[{"name":"Steven M. Boker","is_ca":false},{"name":"Michael C. Neale","is_ca":false},{"name":"Hermine H. Maes","is_ca":false},{"name":"Michael Wilde","is_ca":false},{"name":"Michael Spiegel","is_ca":false},{"name":"Timothy R. Brick","is_ca":false},{"name":"Jeffrey R. Spies","is_ca":false},{"name":"Ryne Estabrook","is_ca":false},{"name":"Sarah Kenny","is_ca":false},{"name":"Timothy C. Bates","is_ca":false},{"name":"Paras Mehta","is_ca":false},{"name":"John Fox","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.4692282198235429,"gpt":0.4921323034118371,"spread":0.02290408358829416,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01666854,0.002407141,0.002043121,0.003127836,0.001080436,0.002614669,0.004510234,0.001514442,0.04444541],"category_scores_gemma":[0.04258768,0.001934291,0.004048266,0.003786877,0.0007815582,0.003429449,0.005846736,0.003818078,0.008074742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001101029,"about_ca_system_score_gemma":0.004267049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004316647,"about_ca_topic_score_gemma":0.006067081,"domain_scores_codex":[0.9907386,0.006628637,0.0006079287,0.0007400278,0.00109154,0.0001933267],"domain_scores_gemma":[0.9731691,0.02217381,0.001261499,0.001495132,0.001556466,0.0003438714],"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":[0.0007236066,0.0005326114,0.007967689,0.003939086,0.00234362,0.0006622246,0.004907167,0.02793956,0.002116916,0.2947268,0.1387538,0.5153869],"study_design_scores_gemma":[0.0004828638,0.0003782466,0.01015227,0.001041332,0.0006713068,0.0005906289,0.0005893179,0.1351428,0.001706306,0.5399381,0.3089533,0.0003535041],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.003070465,0.0004172195,0.9707051,0.0009520845,0.0001269822,0.0006537986,0.0111257,0.01014034,0.002808236],"genre_scores_gemma":[0.01625142,0.0003734026,0.9689998,0.0002182444,0.00007227357,0.00449877,0.006330037,0.001451366,0.001804687],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.04444541,"threshold_uncertainty_score":0.1486847,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2145541966","doi":"10.1016/j.csda.2004.06.015","title":"How many principal components? stopping rules for determining the number of non-trivial axes revisited","year":2004,"lang":"en","type":"article","venue":"Computational Statistics & Data Analysis","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":835,"is_retracted":false,"has_abstract":false,"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; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Principal component analysis; Uncorrelated; Variation (astronomy); Variance (accounting); Mathematics; Set (abstract data type); Statistics; Data set; Total variation; Field (mathematics); Computer science; Data mining; Algorithm","authors":[{"name":"Pedro R. Peres‐Neto","is_ca":true},{"name":"Donald A. Jackson","is_ca":true},{"name":"Keith M. Somers","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1513757986669602,"gpt":0.434713691517873,"spread":0.2833378928509128,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04943797,0.002656631,0.005470429,0.005456249,0.003561597,0.009526026,0.007595274,0.005296805,0.004039263],"category_scores_gemma":[0.2536679,0.002323383,0.002470226,0.004165411,0.005776469,0.01056551,0.005631469,0.01244082,0.001551553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001486659,"about_ca_system_score_gemma":0.00325136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002285157,"about_ca_topic_score_gemma":0.003313674,"domain_scores_codex":[0.9770283,0.01174685,0.002628769,0.003684842,0.00389529,0.001015964],"domain_scores_gemma":[0.7148733,0.2370704,0.008196671,0.01591642,0.01895468,0.004988506],"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":[0.002553958,0.0004824987,0.02571765,0.001649018,0.0008257288,0.0008181469,0.001832088,0.06555273,0.008378847,0.3248318,0.01398817,0.5533693],"study_design_scores_gemma":[0.0003163768,0.0001934579,0.003755915,0.0004964338,0.0002481069,0.0005158622,0.0003160494,0.4760716,0.005537211,0.5073779,0.004982413,0.0001887817],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01653899,0.001540051,0.9786704,0.001254419,0.000136537,0.00008806137,0.00008632667,0.0004724137,0.001212676],"genre_scores_gemma":[0.1484651,0.00110252,0.8452049,0.0006768195,0.0004225858,0.0004254265,0.0004599277,0.0009588519,0.00228383],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04943797,"threshold_uncertainty_score":0.2614561,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2805627121","doi":"10.1038/s41592-018-0019-x","title":"The curse(s) of dimensionality","year":2018,"lang":"en","type":"article","venue":"Nature Methods","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":477,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Curse of dimensionality; Curse; Computational biology; Biology; Evolutionary biology; Computer science; Artificial intelligence; Philosophy","authors":[{"name":"Naomi Altman","is_ca":false},{"name":"Martin Krzywinski","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1031038914002407,"gpt":0.593260094095845,"spread":0.4901562026956043,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02457078,0.002085809,0.003930255,0.004280881,0.002262218,0.007823913,0.003353173,0.004047011,0.007610704],"category_scores_gemma":[0.1930017,0.001606036,0.001769818,0.0043363,0.01410412,0.02284922,0.009923578,0.01398223,0.002578106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002229418,"about_ca_system_score_gemma":0.003460791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002422691,"about_ca_topic_score_gemma":0.002362337,"domain_scores_codex":[0.9658855,0.01460232,0.002654868,0.006091013,0.01006509,0.0007012602],"domain_scores_gemma":[0.8133402,0.144562,0.004968668,0.02430028,0.0109911,0.001837661],"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":[0.0001605605,0.00006573397,0.00340577,0.001993055,0.0003703145,0.0003552675,0.001290683,0.007505022,0.00178335,0.8538502,0.03839576,0.09082429],"study_design_scores_gemma":[0.000030653,0.00006284568,0.001198514,0.0003454791,0.0000766976,0.0006156872,0.0001806521,0.02531753,0.0007581699,0.9447906,0.02653027,0.00009287246],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01746099,0.04006211,0.8571029,0.04184019,0.006065319,0.0001957746,0.002456517,0.001141452,0.03367487],"genre_scores_gemma":[0.452318,0.04801723,0.4259145,0.01788434,0.01692543,0.001948986,0.002034458,0.001973791,0.03298322],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02457078,"threshold_uncertainty_score":0.1299443,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2741038359","doi":"10.1038/nmeth.4370","title":"Classification and regression trees","year":2017,"lang":"en","type":"article","venue":"Nature Methods","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":382,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Regression; Computational biology; Regression analysis; Biology; Computer science; Artificial intelligence; Statistics; Machine learning; Mathematics","authors":[{"name":"Martin Krzywinski","is_ca":true},{"name":"Naomi Altman","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2042817623890058,"gpt":0.5828584757523744,"spread":0.3785767133633685,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004463369,0.001057273,0.001932514,0.002540491,0.0009201484,0.002816487,0.001816633,0.002390185,0.008960923],"category_scores_gemma":[0.01890119,0.0006905267,0.001553321,0.003099445,0.00145636,0.003831836,0.001841183,0.00378542,0.007146947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007950606,"about_ca_system_score_gemma":0.001103926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009778859,"about_ca_topic_score_gemma":0.001074637,"domain_scores_codex":[0.9951933,0.00209243,0.0002824164,0.001062602,0.00119484,0.0001744077],"domain_scores_gemma":[0.9912196,0.004939184,0.0006340626,0.00192767,0.001084761,0.0001947936],"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":[0.00008826317,0.0001286664,0.002072093,0.0005255295,0.0002320315,0.0001134501,0.0001820753,0.03260804,0.002121162,0.390457,0.04026121,0.5312107],"study_design_scores_gemma":[0.0000198827,0.00004616294,0.001181864,0.0001087722,0.00009669973,0.0002394362,0.00004977006,0.34992,0.001418831,0.6016571,0.04523129,0.00003028196],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004327367,0.005559171,0.977689,0.001919739,0.0009235212,0.00006231821,0.0004826229,0.001075532,0.007960672],"genre_scores_gemma":[0.1966206,0.008164478,0.7350039,0.002104682,0.004817405,0.0006331523,0.003495317,0.001133603,0.04802686],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008960923,"threshold_uncertainty_score":0.02997732,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2782098519","doi":"10.1038/nmeth.4551","title":"Machine learning: supervised methods","year":2018,"lang":"en","type":"article","venue":"Nature Methods","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":337,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"National Institute of Mental Health","keywords":"Computer science; Machine learning; Artificial intelligence; Computational biology; Biology","authors":[{"name":"Danilo Bzdok","is_ca":false},{"name":"Martin Krzywinski","is_ca":true},{"name":"Naomi Altman","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1092847856395517,"gpt":0.5430386300648095,"spread":0.4337538444252578,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003930425,0.001311889,0.001974431,0.001926282,0.0006670684,0.003245694,0.002335957,0.00263546,0.009249214],"category_scores_gemma":[0.01652329,0.0008769095,0.001183658,0.00252002,0.001822829,0.003668671,0.0030736,0.005401482,0.01102174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008931452,"about_ca_system_score_gemma":0.001713108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005233508,"about_ca_topic_score_gemma":0.0007798478,"domain_scores_codex":[0.9951577,0.002342031,0.0002571164,0.0009663788,0.001182509,0.00009430788],"domain_scores_gemma":[0.9915234,0.004651348,0.0004464753,0.001961284,0.001210651,0.0002069257],"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":[0.00006779406,0.0001724271,0.0008119177,0.001657729,0.0002057092,0.00009092929,0.0001452418,0.03188498,0.001768566,0.2334694,0.09355584,0.6361694],"study_design_scores_gemma":[0.00003370805,0.00003505403,0.0006663823,0.0002770073,0.00006274933,0.0002943245,0.00004410636,0.3349596,0.002172288,0.5877841,0.07362077,0.00004999307],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0007678173,0.004736723,0.9876568,0.0009734045,0.0004351736,0.00004254588,0.0002265584,0.001241267,0.003919682],"genre_scores_gemma":[0.0550506,0.007844029,0.9121589,0.001028924,0.002722189,0.0006851376,0.001354816,0.001272719,0.01788273],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009249214,"threshold_uncertainty_score":0.03094167,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2027900864","doi":"10.3758/s13428-012-0289-7","title":"SPSS and SAS programs for comparing Pearson correlations and OLS regression coefficients","year":2013,"lang":"en","type":"article","venue":"Behavior Research Methods","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":287,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"NOSM University; Lakehead University","funders":"","keywords":"Rounding; Raw data; Computer science; Statistics; Pearson product-moment correlation coefficient; Regression analysis; Regression; Software; Data mining; Mathematics; Programming language","authors":[{"name":"Bruce Weaver","is_ca":true},{"name":"Karl L. Wuensch","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.6740604188140626,"gpt":0.6686980108350041,"spread":0.005362407979058514,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0121569,0.001470509,0.001991292,0.004688128,0.0009129455,0.002028451,0.001683562,0.0008712793,0.08317594],"category_scores_gemma":[0.1042837,0.0010031,0.001895316,0.005512815,0.000821378,0.001855235,0.001455923,0.004039407,0.01579506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008840426,"about_ca_system_score_gemma":0.004187015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002462547,"about_ca_topic_score_gemma":0.004388659,"domain_scores_codex":[0.9828996,0.008325999,0.002312609,0.001525621,0.00424116,0.0006950343],"domain_scores_gemma":[0.8533656,0.1160344,0.008581193,0.01232885,0.008885411,0.0008046172],"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":[0.002126862,0.002117512,0.03001766,0.004153195,0.001272696,0.0005226677,0.00391155,0.006126064,0.00519319,0.06703836,0.3528089,0.5247113],"study_design_scores_gemma":[0.001816932,0.004245288,0.1324662,0.002435705,0.002171271,0.00180797,0.006434797,0.06314035,0.0303635,0.1560548,0.5984094,0.0006538559],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06203182,0.0005360874,0.7245645,0.001170793,0.001812372,0.006146688,0.08761439,0.05927023,0.05685313],"genre_scores_gemma":[0.1318375,0.0005984352,0.7596003,0.0006202571,0.0003519877,0.03503447,0.02325575,0.01779232,0.03090894],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.08317594,"threshold_uncertainty_score":0.2782512,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2948497811","doi":"","title":"Applied regression analysis and generalized linear models, 2nd ed.","year":2008,"lang":"en","type":"article","venue":"","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":183,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Linear regression; Proper linear model; Regression analysis; Linear model; Mathematics; Generalized linear model; Statistics; Computer science; Bayesian multivariate linear regression; Econometrics","authors":[{"name":"John Fox","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1407686489088452,"gpt":0.4000305764926803,"spread":0.2592619275838351,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003506236,0.003516634,0.003846724,0.003860023,0.0005769531,0.002230247,0.002205879,0.002051409,0.02291757],"category_scores_gemma":[0.0103185,0.001971913,0.002385362,0.004035098,0.001857187,0.002917958,0.001550355,0.004066942,0.0135671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008579036,"about_ca_system_score_gemma":0.001448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002747834,"about_ca_topic_score_gemma":0.004349325,"domain_scores_codex":[0.99827,0.0005698052,0.0002589468,0.000289506,0.0005473629,0.00006424535],"domain_scores_gemma":[0.994091,0.003725129,0.000437405,0.0008548946,0.0007985082,0.00009310375],"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":[0.0001269926,0.0002021378,0.0016127,0.005048304,0.0005773168,0.0005728555,0.0005507543,0.02200755,0.003459845,0.1093741,0.3331209,0.5233466],"study_design_scores_gemma":[0.00006012263,0.0002128463,0.004091703,0.001433641,0.0004812682,0.002407343,0.0002630337,0.03185745,0.002604995,0.3048473,0.6515437,0.0001965569],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001886738,0.3225135,0.6390719,0.003778518,0.00774214,0.0001227265,0.003362748,0.004138694,0.01738306],"genre_scores_gemma":[0.03758495,0.3879659,0.5103598,0.002141497,0.01015083,0.0009919818,0.005513144,0.002256269,0.04303559],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02291757,"threshold_uncertainty_score":0.07666689,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2263152475","doi":"10.22329/amr.v12i3.660","title":"A Truly Multivariate Approach to Manova","year":2009,"lang":"en","type":"article","venue":"Applied Multivariate Research","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":140,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Multivariate analysis of variance; Univariate; Multivariate statistics; Multivariate analysis; Variance (accounting); Set (abstract data type); Statistics; Econometrics; Computer science; Mathematics","authors":[{"name":"James W. Grice","is_ca":false},{"name":"Michiko Iwasaki","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3777742973636383,"gpt":0.5325945615181401,"spread":0.1548202641545018,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02279272,0.001988895,0.001853173,0.003209349,0.00212155,0.006741384,0.00312515,0.001530404,0.01530781],"category_scores_gemma":[0.07989544,0.0008982808,0.001832127,0.005572065,0.004574852,0.004986079,0.005838452,0.0082915,0.006246591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009201001,"about_ca_system_score_gemma":0.004875478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008209359,"about_ca_topic_score_gemma":0.001195037,"domain_scores_codex":[0.9749927,0.01715251,0.001057122,0.003108531,0.003303972,0.000385108],"domain_scores_gemma":[0.9680447,0.01487366,0.002337148,0.008610837,0.005329378,0.0008041579],"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":[0.000174896,0.0002011787,0.00402338,0.002014778,0.0005925184,0.0002502501,0.003633031,0.002123382,0.007443782,0.5146657,0.06583779,0.3990392],"study_design_scores_gemma":[0.00005278778,0.0005719746,0.00630619,0.0007550984,0.0001999736,0.0009743149,0.001058673,0.01343805,0.004816156,0.6086909,0.3629118,0.0002240616],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001354727,0.0006668246,0.9860436,0.001268775,0.0008891409,0.0003161043,0.000408865,0.001798857,0.007253276],"genre_scores_gemma":[0.02503751,0.001246622,0.9637454,0.001175568,0.0008092343,0.00213617,0.0004790724,0.001274738,0.004095654],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02279272,"threshold_uncertainty_score":0.1205409,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2566224772","doi":"10.1038/nmeth.4120","title":"P values and the search for significance","year":2016,"lang":"en","type":"article","venue":"Nature Methods","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":134,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Computational biology; Biology","authors":[{"name":"Naomi Altman","is_ca":false},{"name":"Martin Krzywinski","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1103798670759705,"gpt":0.5364616119471861,"spread":0.4260817448712156,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0714618,0.001952289,0.006178764,0.01084279,0.003478335,0.008831367,0.007440442,0.007602394,0.00930076],"category_scores_gemma":[0.4207824,0.001631498,0.004597147,0.00832684,0.02148524,0.01273168,0.007390694,0.01723184,0.001331392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00218383,"about_ca_system_score_gemma":0.005814386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001498405,"about_ca_topic_score_gemma":0.001025145,"domain_scores_codex":[0.89818,0.06995963,0.005454476,0.01406202,0.0110365,0.001307473],"domain_scores_gemma":[0.447652,0.5238795,0.007430977,0.01407733,0.004497889,0.002462474],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002786062,0.0004312823,0.04103085,0.005827647,0.005545372,0.004193008,0.002801877,0.01117944,0.002619358,0.5897959,0.02076705,0.3130221],"study_design_scores_gemma":[0.0001996434,0.0002123173,0.001575376,0.0003442269,0.0003070647,0.0006690692,0.0003702269,0.0108319,0.000532393,0.9800387,0.004864128,0.00005490999],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.05350025,0.0204498,0.8815643,0.02876673,0.002629712,0.0004449886,0.001246448,0.001125012,0.01027268],"genre_scores_gemma":[0.6508543,0.00389995,0.3292056,0.007181268,0.00310114,0.001528128,0.001003151,0.0005207809,0.002705727],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.9285382,"threshold_uncertainty_score":0.3779306,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4385812426","doi":"10.1038/s41592-023-01973-1","title":"Convolutional neural networks","year":2023,"lang":"en","type":"article","venue":"Nature Methods","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":97,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Convolutional neural network; Computer science; Artificial intelligence; Cognitive science; Psychology","authors":[{"name":"Alexander Derry","is_ca":false},{"name":"Martin Krzywinski","is_ca":true},{"name":"Naomi Altman","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1195731843159488,"gpt":0.5371036006025786,"spread":0.4175304162866297,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004807908,0.0007334233,0.0005167772,0.0007271795,0.0003919416,0.001221942,0.0009327098,0.001118426,0.01059569],"category_scores_gemma":[0.002291839,0.0003977276,0.0004957913,0.0007008026,0.0005281543,0.001428613,0.001110387,0.00134796,0.005129281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008806763,"about_ca_system_score_gemma":0.001173216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005186981,"about_ca_topic_score_gemma":0.006989774,"domain_scores_codex":[0.9996814,0.00004233086,0.00001338627,0.0001177685,0.00009808898,0.00004715751],"domain_scores_gemma":[0.9994543,0.0001391111,0.00004504411,0.0001724395,0.0001536258,0.00003552723],"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":[0.0001179882,0.00009321998,0.001556589,0.0002531028,0.000132843,0.00009727033,0.00005114779,0.1246607,0.01328884,0.2244265,0.03947355,0.5958483],"study_design_scores_gemma":[0.00001367243,0.00003477947,0.001128206,0.00006645788,0.00005775465,0.00009929317,0.0000147565,0.8411351,0.009891327,0.1118483,0.03568674,0.00002373306],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01343151,0.002408325,0.9429478,0.0009506937,0.0006582962,0.00008242256,0.00136953,0.0025585,0.03559294],"genre_scores_gemma":[0.4566067,0.004967202,0.3510516,0.001094823,0.0007434422,0.0003043571,0.006442779,0.0008293428,0.1779597],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01059569,"threshold_uncertainty_score":0.03544611,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2136002638","doi":"10.3389/fpsyg.2010.00146","title":"Discriminant analysis for repeated measures data: a review","year":2010,"lang":"en","type":"review","venue":"Frontiers in Psychology","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":40,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Saskatchewan","funders":"Canadian Institutes of Health Research; Manitoba Health Research Council","keywords":"Univariate; Linear discriminant analysis; Discriminative model; Missing data; Repeated measures design; Covariance; Multivariate statistics; Multivariate analysis; Psychology; Statistics; Descriptive statistics; Analysis of covariance; Artificial intelligence; Computer science; Data mining; Machine learning; Mathematics","authors":[{"name":"Lisa M. Lix","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.4304565299187252,"gpt":0.5703648247814097,"spread":0.1399082948626845,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0095449,0.001742908,0.003426089,0.005415302,0.0004514675,0.001706714,0.00284502,0.001288794,0.005474441],"category_scores_gemma":[0.01939938,0.0006404672,0.001761273,0.006691174,0.001688706,0.001863141,0.001028785,0.001696326,0.004194031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001321765,"about_ca_system_score_gemma":0.002342379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002269357,"about_ca_topic_score_gemma":0.001974833,"domain_scores_codex":[0.9952749,0.001623626,0.0005121401,0.0007128401,0.001803913,0.00007252976],"domain_scores_gemma":[0.9789433,0.01630865,0.001074225,0.0005722836,0.002943362,0.0001582283],"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":[0.00004439723,0.00006589691,0.0009404816,0.01225562,0.0002007337,0.00006705335,0.0001395541,0.0004816822,0.0004790467,0.004272958,0.01102645,0.9700263],"study_design_scores_gemma":[0.00007054213,0.0004863319,0.01883394,0.01854669,0.001109159,0.003189839,0.0006178315,0.004605523,0.003917501,0.03881122,0.9094889,0.0003223612],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0006855079,0.9625158,0.03218382,0.0008950391,0.0004510121,0.00008908923,0.0002119916,0.0001832824,0.002784546],"genre_scores_gemma":[0.00659353,0.9598719,0.030505,0.0003232506,0.0007300415,0.0002429524,0.0003510837,0.00009175623,0.001290459],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.0095449,"threshold_uncertainty_score":0.05047882,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W320664247","doi":"10.1007/s11356-015-4664-7","title":"An open-source software package for multivariate modeling and clustering: applications to air quality management","year":2015,"lang":"en","type":"article","venue":"Environmental Science and Pollution Research","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":30,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"R package; Multivariate statistics; Cluster analysis; Tree (set theory); Software; Computer science; Data mining; Variance (accounting); Multivariate analysis of variance; Software package; Multivariate analysis; Sample (material); Statistics; Mathematics; Machine learning","authors":[{"name":"Xiuquan Wang","is_ca":true},{"name":"Guohe Huang","is_ca":true},{"name":"Shan Zhao","is_ca":true},{"name":"Junhong Guo","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3602249742204898,"gpt":0.5328251620441696,"spread":0.1726001878236798,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00319966,0.002854909,0.002587902,0.00240348,0.001371833,0.002470358,0.005138324,0.001922356,0.06425732],"category_scores_gemma":[0.01240491,0.002113242,0.003460244,0.003120272,0.0005468855,0.00226023,0.00329925,0.00374507,0.03008421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007890719,"about_ca_system_score_gemma":0.003384335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007468638,"about_ca_topic_score_gemma":0.01238554,"domain_scores_codex":[0.9983491,0.0004798768,0.0002349238,0.0003555227,0.0004391612,0.000141419],"domain_scores_gemma":[0.994429,0.00344549,0.0003686709,0.0006352171,0.0008952181,0.0002264021],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000726444,0.0005946045,0.003563876,0.003080473,0.001475502,0.0004275391,0.0007986359,0.03154075,0.008605266,0.01667697,0.4737237,0.4587863],"study_design_scores_gemma":[0.001026157,0.0002883761,0.009478225,0.0005697743,0.0008292342,0.001234085,0.000224305,0.4631248,0.0226183,0.07360822,0.426501,0.0004974561],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.002068264,0.0002980975,0.7748225,0.0002644504,0.0002860518,0.0003546948,0.02015086,0.1992027,0.002552369],"genre_scores_gemma":[0.01261064,0.0004185962,0.9144244,0.000342404,0.0001358013,0.002413539,0.01894002,0.04420996,0.006504687],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.06425732,"threshold_uncertainty_score":0.2149622,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1530376179","doi":"","title":"An Invitation to Multivariate Analysis: An Example About the Effect of Educational Attainment on Migration Propensities in Japan","year":2003,"lang":"en","type":"article","venue":"Social and Economic Dimensions of an Aging Population Research Papers","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":24,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Multivariate statistics; Contradiction; Educational attainment; Multivariate analysis; Econometrics; Logistic regression; Control (management); Inference; Psychology; Statistics; Computer science; Economics; Mathematics; Artificial intelligence; Economic growth; Epistemology","authors":[{"name":"Atsushi Otomo","is_ca":true},{"name":"Kao‐Lee Liaw","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1360982558664185,"gpt":0.4652626986906017,"spread":0.3291644428241832,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01349261,0.000419826,0.0005541088,0.001263511,0.001394047,0.001146573,0.0004673405,0.0006421795,0.004408596],"category_scores_gemma":[0.05113965,0.0001927541,0.001208589,0.002501938,0.002758621,0.001174981,0.002447431,0.002211129,0.000191285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007368132,"about_ca_system_score_gemma":0.0006956576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006182486,"about_ca_topic_score_gemma":0.01080258,"domain_scores_codex":[0.9908683,0.007948725,0.0002001135,0.0003044124,0.0005566179,0.0001218489],"domain_scores_gemma":[0.9583906,0.03451559,0.002733263,0.002215977,0.00172956,0.0004148829],"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":[0.0009979274,0.0003683955,0.288824,0.0007862831,0.001108524,0.006786547,0.02379308,0.008755565,0.003532018,0.3158209,0.05360106,0.2956257],"study_design_scores_gemma":[0.0001754248,0.0006794713,0.405766,0.0005658116,0.0009198789,0.003946024,0.01386484,0.05246289,0.00358716,0.3899547,0.1276229,0.0004549301],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4761877,0.005202215,0.3312355,0.1575304,0.001332858,0.0001223988,0.0005761381,0.0004034666,0.02740926],"genre_scores_gemma":[0.9275079,0.002417336,0.05553132,0.00673831,0.001400989,0.000140634,0.0001143518,0.0002361063,0.005913088],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01349261,"threshold_uncertainty_score":0.07135653,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4317739163","doi":"10.3390/sym15020318","title":"Ratio Data: Understanding Pitfalls and Knowing When to Standardise","year":2023,"lang":"en","type":"article","venue":"Symmetry","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":23,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary; Jewish General Hospital","funders":"","keywords":"Variable (mathematics); Value (mathematics); Component (thermodynamics); Computer science; Metric (unit); Mathematics; Statistics; Mathematical analysis; Operations management; Physics; Engineering","authors":[{"name":"Chris Bishop","is_ca":false},{"name":"Ian Shrier","is_ca":true},{"name":"Matthew J. Jordan","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3713116979787804,"gpt":0.4629078722222664,"spread":0.09159617424348598,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.111364,0.001734548,0.002708405,0.007456633,0.001637912,0.01188742,0.004729675,0.003677239,0.007285079],"category_scores_gemma":[0.4972895,0.001437829,0.001597029,0.009326397,0.01293288,0.02216102,0.00583267,0.007393518,0.005477463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002127641,"about_ca_system_score_gemma":0.002819853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002009448,"about_ca_topic_score_gemma":0.001586186,"domain_scores_codex":[0.8887926,0.07276836,0.008976401,0.009106345,0.0196051,0.0007511487],"domain_scores_gemma":[0.6559148,0.234033,0.02519268,0.05132151,0.03190057,0.001637471],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004814064,0.00007172451,0.01258784,0.00157644,0.000592036,0.0004147011,0.004019029,0.002951718,0.00174992,0.5190579,0.05515855,0.4013388],"study_design_scores_gemma":[0.00008227685,0.0001745283,0.003162608,0.001079222,0.00013091,0.00107393,0.001118984,0.008892248,0.002871841,0.905916,0.07528035,0.0002171691],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009699119,0.009346443,0.9400429,0.02283082,0.002486869,0.0003174209,0.001907559,0.002076232,0.01129272],"genre_scores_gemma":[0.2043974,0.007997401,0.7635277,0.01045061,0.003989791,0.001159765,0.001684189,0.002525244,0.004267802],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.888636,"threshold_uncertainty_score":0.5889562,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2278388756","doi":"10.7717/peerj.1720","title":"A comparison of clustering methods for biogeography with fossil datasets","year":2016,"lang":"en","type":"article","venue":"PeerJ","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":18,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Royal Ontario Museum","funders":"","keywords":"Cluster analysis; Hierarchical clustering; Euclidean distance; Computer science; Set (abstract data type); Complete-linkage clustering; Data mining; Similarity (geometry); Cluster (spacecraft); Complete linkage; Single-linkage clustering; Data set; Range (aeronautics); Mathematics; Fuzzy clustering; Artificial intelligence; Biology; CURE data clustering algorithm","authors":[{"name":"Matthew J. Vavrek","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2099705058052693,"gpt":0.5469419897198773,"spread":0.336971483914608,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.035514,0.001462985,0.001503983,0.007634901,0.001522346,0.002793503,0.003189982,0.001816921,0.004784268],"category_scores_gemma":[0.09682145,0.0006669181,0.002336758,0.007900693,0.001038681,0.003670615,0.002452232,0.001933586,0.002329917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002120133,"about_ca_system_score_gemma":0.002587966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006800317,"about_ca_topic_score_gemma":0.007127841,"domain_scores_codex":[0.972769,0.01670169,0.001376248,0.002286074,0.00647449,0.0003926243],"domain_scores_gemma":[0.9324544,0.050496,0.001940926,0.00629316,0.008192325,0.0006231967],"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":[0.002302994,0.0003716521,0.0200475,0.004515328,0.00365149,0.0002573551,0.002579028,0.1901378,0.004812865,0.05178551,0.03436537,0.685173],"study_design_scores_gemma":[0.0003908353,0.0007402872,0.02808777,0.001491482,0.0004297561,0.0007403556,0.001533549,0.8176283,0.006583587,0.07387314,0.06803896,0.0004619923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06282783,0.007475921,0.9075168,0.001409748,0.0009823531,0.0009394498,0.003649514,0.00552306,0.009675411],"genre_scores_gemma":[0.1068096,0.003506221,0.8778287,0.0001781645,0.0001515067,0.001404897,0.00545814,0.002650268,0.002012574],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.035514,"threshold_uncertainty_score":0.1878182,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2970227126","doi":"10.17060/ijodaep.2019.n1.v5.1641","title":"Análisis de clases latentes como técnica de identificación de tipologías","year":2019,"lang":"es","type":"article","venue":"International Journal of Developmental and Educational Psychology Revista INFAD de psicología","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Innovation Cluster (Canada)","funders":"","keywords":"Humanities; Philosophy; Sociology","authors":[{"name":"Daniel Ondé","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.041153385054976,"gpt":0.426761970707177,"spread":0.385608585652201,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02052703,0.002003406,0.001895602,0.007447759,0.001473135,0.004108257,0.001764546,0.001176211,0.00989413],"category_scores_gemma":[0.06220691,0.0009408896,0.003551228,0.007342138,0.001809683,0.003679827,0.002822203,0.002503242,0.001791805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001930318,"about_ca_system_score_gemma":0.004135828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01124986,"about_ca_topic_score_gemma":0.01245386,"domain_scores_codex":[0.9794855,0.01097578,0.001580069,0.003044691,0.004363457,0.0005506359],"domain_scores_gemma":[0.9396654,0.03690501,0.008239713,0.006932907,0.007658347,0.0005985937],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007847828,0.0007812261,0.4712786,0.005123617,0.004443999,0.0002887591,0.0137794,0.007342843,0.01250708,0.02610285,0.005617264,0.4519496],"study_design_scores_gemma":[0.0001906101,0.002997466,0.7030288,0.004057213,0.002865386,0.001121782,0.02859824,0.06908654,0.02723609,0.09244515,0.06777894,0.0005937275],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3607291,0.005453152,0.5959037,0.001537445,0.000415504,0.003773178,0.008518611,0.001302455,0.0223668],"genre_scores_gemma":[0.6999736,0.002426474,0.2817515,0.0002830481,0.0001221899,0.004105861,0.003509364,0.0002852956,0.007542703],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02052703,"threshold_uncertainty_score":0.1085587,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1994960304","doi":"10.1016/j.ecolmodel.2008.11.006","title":"A new procedure to optimize the selection of groups in a classification tree: Applications for ecological data","year":2008,"lang":"en","type":"article","venue":"Ecological Modelling","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Ministère de l'Enseignement Supérieur et de la Recherche; European Commission; Gordon and Betty Moore Foundation","keywords":"Outlier; Robustness (evolution); Computer science; Ecology; Tree (set theory); Statistics; Artificial intelligence; Biology; Data mining; Mathematics; Combinatorics","authors":[{"name":"Lionel Guidi","is_ca":false},{"name":"Frédéric Ibañez","is_ca":false},{"name":"Vincent Calcagno","is_ca":true},{"name":"Grégory Beaugrand","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3670749276056314,"gpt":0.4170840400753615,"spread":0.05000911246973011,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01288948,0.00187052,0.003426373,0.003057008,0.001792378,0.002250362,0.004058204,0.002973727,0.002943199],"category_scores_gemma":[0.02091002,0.001169022,0.002452518,0.004272484,0.00183837,0.002770223,0.003557815,0.005112019,0.001658186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009989423,"about_ca_system_score_gemma":0.002182072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003061705,"about_ca_topic_score_gemma":0.0057263,"domain_scores_codex":[0.9937225,0.002862937,0.0005632726,0.001467661,0.001168972,0.0002146043],"domain_scores_gemma":[0.9893335,0.005643183,0.0008381043,0.001642703,0.002130009,0.0004126529],"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":[0.0003938093,0.0005098662,0.003730713,0.0003355437,0.0005852469,0.0001030426,0.0005839282,0.08289757,0.01473626,0.01926802,0.01328682,0.8635693],"study_design_scores_gemma":[0.0002832832,0.000285596,0.002425268,0.00007134911,0.0002758735,0.0002863981,0.000104491,0.935999,0.005463433,0.04703346,0.007659648,0.0001122777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002358867,0.00008978262,0.9966943,0.00008492329,0.00003953701,0.00007780894,0.00007180219,0.0004844331,0.00009864275],"genre_scores_gemma":[0.01329558,0.00004892998,0.9854397,0.00008274951,0.00007133964,0.0002351802,0.0002354292,0.0002612566,0.0003298105],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01288948,"threshold_uncertainty_score":0.06816685,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4241339529","doi":"10.1007/bf02295616","title":"T. Hastie, R. Tibshirani, and J. Friedman. The elements of statistical learning: Data mining, inference, and prediction. New York, NY: Springer, 2001, 533 + xvi pp., $79.95.","year":2003,"lang":"en","type":"article","venue":"Psychometrika","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":14,"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":"Psychology; Mathematics; Statistics; Econometrics","authors":[{"name":"Jim Ramsay","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2257847661070508,"gpt":0.412629087590875,"spread":0.1868443214838242,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01107273,0.004010981,0.003575069,0.01080258,0.001897653,0.003346219,0.003972598,0.003355342,0.0361495],"category_scores_gemma":[0.03958364,0.003454244,0.002335211,0.01160127,0.005826317,0.006935882,0.001985123,0.006516492,0.0303097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002011863,"about_ca_system_score_gemma":0.002610727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009814881,"about_ca_topic_score_gemma":0.01378092,"domain_scores_codex":[0.9955236,0.001830005,0.0004665917,0.0004991752,0.001533071,0.0001475333],"domain_scores_gemma":[0.9727191,0.02062487,0.001450261,0.001600278,0.003114623,0.0004908029],"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":[0.0003194892,0.0001366225,0.001727631,0.002503422,0.0004867934,0.0002327781,0.0005599229,0.005315038,0.0005372848,0.02444096,0.5691792,0.3945608],"study_design_scores_gemma":[0.0002922181,0.0004760467,0.01141568,0.002610629,0.001148932,0.001781816,0.0004743416,0.01245475,0.004432477,0.2548387,0.709401,0.0006733231],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001789914,0.7244791,0.2264553,0.01382932,0.01518239,0.0001757799,0.003823278,0.001650907,0.01261392],"genre_scores_gemma":[0.03240261,0.6782234,0.2296234,0.00322088,0.02059347,0.0009037554,0.006280286,0.001881283,0.02687085],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.0361495,"threshold_uncertainty_score":0.1209321,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3148764640","doi":"10.1111/dsji.12233","title":"Generating data sets for teaching the importance of regression analysis","year":2021,"lang":"en","type":"article","venue":"Decision Sciences Journal of Innovative Education","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"The King's University; Western University","funders":"","keywords":"Computer science; Descriptive statistics; Regression analysis; Statistical inference; Linear regression; Statistics; Multivariate statistics; Statistical analysis; Simple linear regression; Data mining; Machine learning; Mathematics","authors":[{"name":"Lori L. Murray","is_ca":true},{"name":"John G. Wilson","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3069078638950074,"gpt":0.5791005695762698,"spread":0.2721927056812624,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02845756,0.001289169,0.0007809008,0.002925584,0.0008007132,0.003014541,0.002760456,0.001137222,0.0176775],"category_scores_gemma":[0.2055248,0.0007571793,0.001272161,0.002412673,0.001087807,0.003068497,0.003046198,0.005592661,0.006399714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001098065,"about_ca_system_score_gemma":0.001760168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004811727,"about_ca_topic_score_gemma":0.0007610447,"domain_scores_codex":[0.9799952,0.01384376,0.001056074,0.001289972,0.003624181,0.0001908077],"domain_scores_gemma":[0.7836066,0.1847286,0.004694764,0.01435644,0.01152202,0.001091466],"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":[0.0004371738,0.0008194423,0.006215343,0.001819906,0.0001786976,0.0006304291,0.004713985,0.03425586,0.01042214,0.1687997,0.1549785,0.6167287],"study_design_scores_gemma":[0.0005065292,0.0004885052,0.003965129,0.001647333,0.0001180998,0.0006844745,0.001436483,0.3022425,0.03260623,0.4234082,0.2326241,0.00027231],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004515897,0.00008087367,0.9849232,0.002220749,0.0002628864,0.0006754551,0.0008400513,0.003265645,0.003215186],"genre_scores_gemma":[0.02366727,0.0001532259,0.9714838,0.0004642528,0.0001216151,0.001571332,0.000592944,0.001128908,0.0008166042],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02845756,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"labels":[{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"high"},{"model":"opus","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"high"}],"label_agreement":"split"},{"id":"W2954305130","doi":"10.5539/ijsp.v8n4p32","title":"Simultaneous Hypothesis Testing of Multivariable Nonparametric Spline Regression in the GWR Model","year":2019,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Statistics; Nonparametric statistics; Mathematics; Nonparametric regression; Statistical hypothesis testing; Test statistic; Statistic; Regression analysis; Likelihood-ratio test; Econometrics","authors":[{"name":"Sifriyani Sifriyani","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.09760816354157696,"gpt":0.38297873878188,"spread":0.285370575240303,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0332699,0.001338821,0.003014697,0.001803681,0.0009300741,0.002435419,0.002805072,0.001716354,0.007682781],"category_scores_gemma":[0.08183464,0.0006908673,0.003225679,0.002103048,0.002817942,0.002548339,0.002529864,0.002767385,0.0005720821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009119518,"about_ca_system_score_gemma":0.002849426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00283655,"about_ca_topic_score_gemma":0.001411327,"domain_scores_codex":[0.9497626,0.03639659,0.001343973,0.006717822,0.003853138,0.001925901],"domain_scores_gemma":[0.9214212,0.06858928,0.003676779,0.003379935,0.002346564,0.000586286],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002676013,0.001069371,0.2012543,0.001669854,0.0068318,0.004669051,0.002688656,0.2725749,0.003990034,0.2326751,0.006250048,0.2636509],"study_design_scores_gemma":[0.0002020987,0.001297551,0.02290307,0.0001440515,0.0005542916,0.0005043669,0.0006987755,0.8811257,0.001376641,0.08793793,0.003169216,0.00008634718],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1593562,0.0005785062,0.8355828,0.0008341463,0.0003106309,0.0002930238,0.0005732558,0.0004342963,0.002037124],"genre_scores_gemma":[0.9181829,0.0003508668,0.0772448,0.0002015839,0.0001748806,0.0007921321,0.0006725626,0.00007941376,0.002300725],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0332699,"threshold_uncertainty_score":0.1759501,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2165746155","doi":"10.1007/s11156-009-0123-1","title":"Binary response and logistic regression in recent accounting research publications: a methodological note","year":2009,"lang":"en","type":"article","venue":"Review of Quantitative Finance and Accounting","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University; University of Manitoba","funders":"","keywords":"Logistic regression; Regression diagnostic; Econometrics; Regression analysis; Presentation (obstetrics); Ordinary least squares; Linear regression; Variables; Statistics; Accounting; Computer science; Mathematics; Economics; Polynomial regression; Medicine","authors":[{"name":"Wenxia Ge","is_ca":true},{"name":"G. À. Whitmore","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.638020466979831,"gpt":0.6192974701062952,"spread":0.01872299687353574,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.07347815,0.0006269209,0.00122286,0.01929511,0.002003694,0.01249438,0.002477801,0.002865514,0.004845037],"category_scores_gemma":[0.1936662,0.0006500061,0.001175122,0.04497007,0.005817441,0.01066945,0.003450851,0.002734346,0.001325108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001928637,"about_ca_system_score_gemma":0.005025247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00282253,"about_ca_topic_score_gemma":0.005288084,"domain_scores_codex":[0.9417374,0.03954071,0.005066343,0.004335242,0.008495684,0.0008246276],"domain_scores_gemma":[0.5768071,0.349689,0.02404681,0.01247603,0.03571568,0.00126535],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003166772,0.0001695628,0.05765996,0.01082725,0.0007773772,0.0004404198,0.005378011,0.0008062033,0.001236294,0.3948678,0.05051242,0.4770081],"study_design_scores_gemma":[0.0001633624,0.0003220744,0.09247513,0.0158413,0.001994692,0.002724621,0.01010965,0.006427766,0.004060596,0.3368779,0.5287039,0.000298964],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"methods","genre_scores_codex":[0.04084527,0.619585,0.1664321,0.1362369,0.009038791,0.0002147458,0.002240155,0.0002228827,0.02518421],"genre_scores_gemma":[0.4069255,0.3721826,0.1376745,0.02738078,0.0352519,0.001087308,0.002216143,0.0005242521,0.01675701],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9265218,"threshold_uncertainty_score":0.3885942,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2061207790","doi":"10.2495/safe-v3-n4-317-331","title":"Cluster analysis of fatal accidents series in the INFOR.MO database: analysis, evidence and research perspectives","year":2013,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Cluster (spacecraft); Database; Forensic engineering; Computer science; Engineering","authors":[{"name":"M. Lombardi","is_ca":false},{"name":"Giovanni Rossi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06835330957222521,"gpt":0.4247265209796116,"spread":0.3563732114073863,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004218353,0.0003879803,0.0005740123,0.01475695,0.0004446626,0.001615837,0.000765242,0.0004203065,0.001527934],"category_scores_gemma":[0.0115951,0.0001224164,0.0005594824,0.0104336,0.00066603,0.0009420813,0.0006937261,0.000334089,0.0002874495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001089071,"about_ca_system_score_gemma":0.001280928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009178421,"about_ca_topic_score_gemma":0.00764136,"domain_scores_codex":[0.9967958,0.001037388,0.0004209782,0.000433107,0.001153502,0.0001591777],"domain_scores_gemma":[0.9866049,0.006786962,0.002268883,0.001138909,0.002887316,0.0003131392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001203534,0.0002571733,0.7202201,0.001892975,0.0006506273,0.0009369128,0.001916118,0.009574362,0.002704782,0.008792726,0.008173929,0.2436767],"study_design_scores_gemma":[0.00004580638,0.0006166857,0.9177846,0.0006539784,0.0006423034,0.001147614,0.005983294,0.04159603,0.006202864,0.0057512,0.01947043,0.0001051138],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9007139,0.008861974,0.05392979,0.001995107,0.0001153364,0.0005569819,0.02205224,0.0006441594,0.01113039],"genre_scores_gemma":[0.9754831,0.001626064,0.01542813,0.00004401721,0.00006633742,0.0001656039,0.006489667,0.00002290335,0.0006742691],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01475695,"threshold_uncertainty_score":0.02230906,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2897288930","doi":"10.3102/1076998618803381","title":"A Note on the Solution Multiplicity of the Vale–Maurelli Intermediate Correlation Equation","year":2018,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":8,"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","funders":"","keywords":"Kurtosis; Skewness; Correlation; Mathematics; Range (aeronautics); Corollary; Applied mathematics; Multiplicity (mathematics); Monte Carlo method; Correlation coefficient; Statistics; Mathematical analysis; Combinatorics; Geometry","authors":[{"name":"Oscar L. Olvera Astivia","is_ca":false},{"name":"Bruno D. Zumbo","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.168753698670039,"gpt":0.4417865701940591,"spread":0.2730328715240201,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02626395,0.001409681,0.001927126,0.001918107,0.001909378,0.003890908,0.003455032,0.00394844,0.01266488],"category_scores_gemma":[0.2144321,0.0009877415,0.003311988,0.001652428,0.004279332,0.006338057,0.005323917,0.01334556,0.002384478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002219748,"about_ca_system_score_gemma":0.003698148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003738731,"about_ca_topic_score_gemma":0.002755298,"domain_scores_codex":[0.9815837,0.01155015,0.0008983054,0.001989472,0.003355924,0.0006224597],"domain_scores_gemma":[0.832273,0.1486171,0.003595271,0.006602287,0.007841838,0.001070408],"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":[0.0001749624,0.00005738802,0.002789687,0.0002372915,0.00008477033,0.0005350751,0.000663758,0.02564754,0.001158301,0.8814385,0.02789319,0.05931959],"study_design_scores_gemma":[0.0001151412,0.0001009149,0.0006917593,0.0003649483,0.00006526119,0.0005055419,0.0001308478,0.2466941,0.002088887,0.7050108,0.04410519,0.0001265582],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004680337,0.001819574,0.9646783,0.01304936,0.001324125,0.0001226561,0.0001336275,0.0003072402,0.01388479],"genre_scores_gemma":[0.111792,0.002519889,0.8665367,0.00435648,0.002003375,0.0009977042,0.0002604902,0.0008226775,0.01071058],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02626395,"threshold_uncertainty_score":0.1388987,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4393086187","doi":"10.1038/s41592-024-02234-5","title":"Comparing classifier performance with baselines","year":2024,"lang":"en","type":"article","venue":"Nature Methods","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Classifier (UML); Computer science; Computational biology; George (robot); Artificial intelligence; Biology","authors":[{"name":"Fadel M. Megahed","is_ca":false},{"name":"Ying‐Ju Chen","is_ca":false},{"name":"L. Allison Jones‐Farmer","is_ca":false},{"name":"Steven E. Rigdon","is_ca":false},{"name":"Martin Krzywinski","is_ca":true},{"name":"Naomi Altman","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1483906697713013,"gpt":0.5096182819771905,"spread":0.3612276122058892,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01122588,0.002438251,0.002463674,0.004546127,0.001925234,0.004670191,0.002609224,0.003862876,0.007157236],"category_scores_gemma":[0.03042899,0.0004884313,0.002296633,0.002453328,0.0008267644,0.005309895,0.002164583,0.003496455,0.01085123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002031735,"about_ca_system_score_gemma":0.002246539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007743906,"about_ca_topic_score_gemma":0.008913456,"domain_scores_codex":[0.9889094,0.002587204,0.000857659,0.003318711,0.003531907,0.0007951726],"domain_scores_gemma":[0.9793402,0.01086032,0.0007524505,0.003782522,0.004561835,0.0007026619],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.007379336,0.001863606,0.03698742,0.002348376,0.003808141,0.0003792493,0.0003468104,0.04595366,0.01662059,0.004069855,0.1388447,0.7413982],"study_design_scores_gemma":[0.001007011,0.007017443,0.05180236,0.0008020736,0.003709617,0.002467763,0.001832697,0.7398177,0.07267097,0.03106404,0.0872894,0.0005188522],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6240066,0.05782833,0.1876273,0.007501769,0.01368815,0.001092663,0.0338253,0.02739528,0.04703464],"genre_scores_gemma":[0.8265869,0.004889776,0.08598384,0.001258176,0.001977765,0.0003812168,0.0586176,0.001685643,0.01861914],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9887741,"threshold_uncertainty_score":0.05936885,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2498254812","doi":"10.1080/10705511.2016.1207180","title":"Analysis of Correlation Matrices Using Scale-Invariant Common Principal Component Models and a Hierarchy of Relationships Between Correlation Matrices","year":2016,"lang":"en","type":"article","venue":"Structural Equation Modeling A Multidisciplinary Journal","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Principal component analysis; Invariant (physics); Correlation; Mathematics; Scale (ratio); Scale invariance; Applied mathematics; Hierarchy; Statistics; Geometry; Physics","authors":[{"name":"Фэй Гу","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2123378440265293,"gpt":0.4079992422006015,"spread":0.1956613981740722,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005643412,0.001559188,0.0009148948,0.003844815,0.0009780863,0.00267465,0.001449383,0.0009438188,0.003515864],"category_scores_gemma":[0.02599279,0.0006134123,0.001710694,0.005330696,0.002465615,0.004559034,0.001779969,0.002362756,0.000928818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001156272,"about_ca_system_score_gemma":0.001840996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006060233,"about_ca_topic_score_gemma":0.004030018,"domain_scores_codex":[0.995456,0.001990402,0.0002043425,0.00101018,0.001092632,0.000246455],"domain_scores_gemma":[0.9907517,0.004714571,0.001407377,0.001427598,0.001474432,0.0002243072],"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":[0.00005106798,0.00009230097,0.00877318,0.000329861,0.0003063897,0.0004301456,0.001009363,0.1162243,0.003937296,0.7234969,0.004237445,0.1411118],"study_design_scores_gemma":[0.00001076883,0.00005961386,0.004227564,0.00005686008,0.00008046731,0.0001832807,0.0001697052,0.6491434,0.0008192972,0.3407958,0.004379231,0.00007410112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007744849,0.0002780917,0.989666,0.0001861135,0.000025231,0.00005555738,0.00008183799,0.000154533,0.001807764],"genre_scores_gemma":[0.4311226,0.001534509,0.562425,0.0001984287,0.0001568614,0.0004314151,0.0005703699,0.0002296623,0.003331139],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006060233,"threshold_uncertainty_score":0.0298456,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1598527759","doi":"10.6126/apmr.2005.10.1.05","title":"Comparative Analysis on an International Survey of ISO 9000 and ISO 14000 Certification","year":2005,"lang":"en","type":"article","venue":"Asia Pacific Management Review","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"ISO 14000; Certification; Business; Statistical analysis; Marketing; Operations management; Engineering; Statistics; Management; Economics; Mathematics","authors":[{"name":"Jeh‐Nan Pan","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1833998741612395,"gpt":0.4601999636124331,"spread":0.2768000894511936,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004824165,0.0001395573,0.0002397262,0.003870836,0.0002053457,0.00063144,0.0001837441,0.0002353525,0.001281887],"category_scores_gemma":[0.01425436,0.0001048428,0.0002200302,0.01060793,0.000246872,0.0006262586,0.0004952942,0.0002303222,0.0003085986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005376729,"about_ca_system_score_gemma":0.0008485322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005615138,"about_ca_topic_score_gemma":0.01062125,"domain_scores_codex":[0.9947578,0.002462722,0.0004735393,0.0003979494,0.001535533,0.0003724012],"domain_scores_gemma":[0.9809921,0.006684615,0.004396461,0.000650936,0.006842037,0.0004337815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001522484,0.0001169011,0.93172,0.0003970104,0.0001192873,0.000118001,0.00496338,0.0002054037,0.0006269966,0.001484766,0.00410848,0.05598752],"study_design_scores_gemma":[0.000003936298,0.0001663937,0.9861773,0.00007027231,0.00003355376,0.00008487348,0.005850445,0.0001431345,0.000165187,0.00004363874,0.007255893,0.000005276378],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.986262,0.001591161,0.0006135323,0.0001938239,0.00001820247,0.0000623482,0.001779135,0.000006941796,0.00947282],"genre_scores_gemma":[0.9928657,0.001757644,0.0006330248,0.0000957397,0.00001770439,0.00008350056,0.003162212,0.000006455713,0.001377972],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005615138,"threshold_uncertainty_score":0.02551293,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2019929444","doi":"10.3758/s13428-012-0204-2","title":"SPSS macros to compare any two fitted values from a regression model","year":2012,"lang":"en","type":"article","venue":"Behavior Research Methods","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"NOSM University; Lakehead University","funders":"","keywords":"Statistics; Mathematics; Polynomial regression; Regression analysis; Linear regression; Regression; Standard error; Macro; Confidence interval; Design matrix; Segmented regression; Computer science","authors":[{"name":"Bruce Weaver","is_ca":true},{"name":"Sacha Dubois","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.7862703712146977,"gpt":0.74524494245617,"spread":0.04102542875852766,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01372703,0.001930518,0.002403858,0.005567037,0.0009661396,0.001737172,0.001806691,0.001196004,0.08818178],"category_scores_gemma":[0.1167075,0.001189848,0.002449777,0.003329286,0.0009234727,0.002503836,0.002548242,0.004125657,0.01429213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008487505,"about_ca_system_score_gemma":0.002059006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001033001,"about_ca_topic_score_gemma":0.001757337,"domain_scores_codex":[0.9831151,0.008000199,0.002906067,0.001716123,0.00361084,0.0006515899],"domain_scores_gemma":[0.791551,0.1832498,0.007272437,0.009695704,0.007319476,0.00091156],"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":[0.004672517,0.003400629,0.034292,0.003435775,0.002046919,0.000887619,0.004899596,0.008412775,0.01208242,0.04960492,0.4445382,0.4317267],"study_design_scores_gemma":[0.002660864,0.005880927,0.1460635,0.001923491,0.002507219,0.001920894,0.007323611,0.1200559,0.0583364,0.1312073,0.5209593,0.00116073],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.122179,0.000232331,0.60809,0.001213189,0.002339496,0.004995714,0.08861301,0.1347738,0.03756353],"genre_scores_gemma":[0.1958174,0.000205897,0.6651148,0.0007710724,0.0003335648,0.03906791,0.03624663,0.04273053,0.01971226],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.08818178,"threshold_uncertainty_score":0.2949975,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1500993271","doi":"10.1080/10543406.2012.701589","title":"A Review of: “<b> <i>Econometric Analysis</i> </b>, Seventh Edition, by W. H. Greene”","year":2012,"lang":"en","type":"review","venue":"Journal of Biopharmaceutical Statistics","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":5,"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":"Econometrics; Econometric model; Econometric analysis; Library science; Economics; Statistics; Mathematical economics; Computer science; Mathematics","authors":[{"name":"Jeffrey S. Hoch","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2745840886976001,"gpt":0.5258364269402303,"spread":0.2512523382426302,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001758917,0.001013458,0.00142602,0.004994245,0.0005434441,0.002509635,0.001096924,0.00154568,0.02246695],"category_scores_gemma":[0.007681237,0.0004601879,0.0006569555,0.009544445,0.0009759287,0.003484207,0.0009339502,0.002994145,0.02678348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001458589,"about_ca_system_score_gemma":0.003944305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004020259,"about_ca_topic_score_gemma":0.01032936,"domain_scores_codex":[0.9989385,0.0001597849,0.0001130099,0.0001268298,0.0006110701,0.00005081397],"domain_scores_gemma":[0.9961659,0.001525625,0.0003151968,0.00008591056,0.001670855,0.0002365556],"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":[0.0000129815,0.00001829826,0.00008949131,0.00398665,0.00002004107,0.00002872566,0.00004207001,0.00009476699,0.0001778295,0.002846705,0.7096625,0.28302],"study_design_scores_gemma":[0.000002126115,0.000009071583,0.0003229989,0.001560271,0.0000103641,0.0001405,0.00002591306,0.00001883821,0.00004278279,0.0009366578,0.9969236,0.000006892259],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00004974859,0.9830694,0.0006514313,0.005791743,0.004291363,0.00001027751,0.0001831546,0.0000375579,0.005915205],"genre_scores_gemma":[0.0006172264,0.9762189,0.0009105614,0.004248464,0.003262384,0.00002499102,0.0003266016,0.00003756712,0.01435326],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.02246695,"threshold_uncertainty_score":0.07515949,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1565185441","doi":"10.5539/mas.v9n8p72","title":"Study of the Relationship between Dependent and Independent Variable Groups by Using Canonical Correlation Analysis with Application","year":2015,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Canonical correlation; Canonical analysis; Canonical correspondence analysis; Mathematics; Correlation; Statistics; Variables","authors":[{"name":"Thanoon Y. Thanoon","is_ca":false},{"name":"Robiah Adnan","is_ca":false},{"name":"Seyed Ehsan Saffari","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1517776799697554,"gpt":0.3823292301919133,"spread":0.230551550222158,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01324589,0.001499933,0.001484894,0.005508645,0.001316723,0.002914295,0.0008911136,0.0006313924,0.009384461],"category_scores_gemma":[0.05156577,0.0003580639,0.001468758,0.00851952,0.001496347,0.002767847,0.001899192,0.001619344,0.001564255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009341514,"about_ca_system_score_gemma":0.003430217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002128136,"about_ca_topic_score_gemma":0.001569769,"domain_scores_codex":[0.9857998,0.006049848,0.001031661,0.002964786,0.003754223,0.000399768],"domain_scores_gemma":[0.9655699,0.02150001,0.002164404,0.003270172,0.007102629,0.0003927844],"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":[0.0005373536,0.0006409599,0.2116903,0.001919114,0.002012354,0.001004892,0.01032803,0.01334731,0.01058275,0.09248359,0.01530366,0.6401497],"study_design_scores_gemma":[0.0001844505,0.002007094,0.4204417,0.001474236,0.001781843,0.002129604,0.01352101,0.2533856,0.02446597,0.1583707,0.121609,0.0006287771],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1564598,0.001496461,0.8134779,0.000531004,0.000344293,0.001566204,0.001836281,0.00172567,0.0225625],"genre_scores_gemma":[0.5922465,0.0009305621,0.3976979,0.0001039879,0.0001605595,0.002933102,0.002518576,0.0003490868,0.003059808],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01324589,"threshold_uncertainty_score":0.07005185,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2061038353","doi":"10.5539/cis.v7n4p21","title":"Geographic Information System for Detecting Spatial Connectivity Brown Planthopper Endemic Areas Using a Combination of Triple Exponential Smoothing - Getis Ord","year":2014,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Exponential smoothing; Computer science; Class (philosophy); Geographic information system; Component (thermodynamics); Spatial analysis; Smoothing; Warning system; Data mining; Preprocessor; Data science; Cartography; Artificial intelligence; Geography; Remote sensing; Computer vision","authors":[{"name":"Sri Yulianto J. P.","is_ca":false},{"name":"Nugraheni Widyawati","is_ca":false},{"name":"D. H. Kristoko","is_ca":false},{"name":"Bistok Hasiholan S.","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04542460502404905,"gpt":0.3182970813139343,"spread":0.2728724762898853,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001425479,0.0006855064,0.0005875472,0.003508031,0.0004130101,0.001289233,0.0007325571,0.0002835993,0.006054652],"category_scores_gemma":[0.004807044,0.0003670685,0.0006274505,0.002587498,0.0001570957,0.001348737,0.00098132,0.0004021569,0.002409127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005310215,"about_ca_system_score_gemma":0.001024692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007696299,"about_ca_topic_score_gemma":0.008513118,"domain_scores_codex":[0.9993285,0.0001054231,0.0001005983,0.0001634621,0.0002624904,0.00003960319],"domain_scores_gemma":[0.9973593,0.0007975058,0.0002392538,0.0005745342,0.0009176873,0.0001116913],"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":[0.001286334,0.0004776699,0.09772194,0.001054849,0.0003150026,0.0003795116,0.0009612184,0.0335153,0.01624286,0.01002505,0.04837692,0.7896433],"study_design_scores_gemma":[0.0002464749,0.0004393094,0.1199306,0.0001431382,0.0003845625,0.0006339538,0.0007441904,0.6752815,0.06857544,0.01302522,0.1203575,0.0002380318],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1142224,0.0002422415,0.6627077,0.00032861,0.00009756324,0.0008695555,0.03365321,0.1740094,0.01386937],"genre_scores_gemma":[0.4333884,0.0003072636,0.5219416,0.0001104625,0.00003127702,0.0008353677,0.03443382,0.002427335,0.006524387],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007696299,"threshold_uncertainty_score":0.02025479,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2892004684","doi":"10.5539/ijsp.v7n6p33","title":"Heteroscedasticity and Model Selection via Partitioning in Fisheries Data","year":2018,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Heteroscedasticity; Ordinary least squares; Generalized least squares; Selection (genetic algorithm); Model selection; Statistics; Mathematics; Set (abstract data type); Data set; Least-squares function approximation; Econometrics; Computer science; Data mining; Mathematical optimization; Artificial intelligence; Estimator","authors":[{"name":"Morteza Marzjarani","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1598710399318501,"gpt":0.4142415229137705,"spread":0.2543704829819204,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03252081,0.001552455,0.001735185,0.00291175,0.001665724,0.002899422,0.002089513,0.001193719,0.001006997],"category_scores_gemma":[0.07240282,0.0008342103,0.002761256,0.003543633,0.001873755,0.002007351,0.002704325,0.002463935,0.0003368075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00167425,"about_ca_system_score_gemma":0.00277685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007884301,"about_ca_topic_score_gemma":0.009027891,"domain_scores_codex":[0.9705076,0.02132376,0.001742668,0.003595363,0.002402743,0.0004277924],"domain_scores_gemma":[0.9494951,0.04204325,0.002465185,0.003874357,0.001915068,0.0002070664],"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":[0.0005923454,0.0002958304,0.1168986,0.001666114,0.003139235,0.001937048,0.004618713,0.3772053,0.007536522,0.07255919,0.005046684,0.4085044],"study_design_scores_gemma":[0.0000875843,0.0003307008,0.03422527,0.0004427072,0.0003876698,0.0004490587,0.001512349,0.8050084,0.00582165,0.1418364,0.009663582,0.0002346203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09437172,0.000820522,0.901675,0.0006545773,0.00008151704,0.0004728071,0.0005697538,0.0004134072,0.0009406434],"genre_scores_gemma":[0.5358135,0.0005641764,0.4591438,0.0003171456,0.00008412093,0.001210109,0.00196128,0.0002417636,0.000664197],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03252081,"threshold_uncertainty_score":0.1719885,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2624643432","doi":"10.22237/jmasm/1193889840","title":"A Comparison of Procedures for the Analysis of Multivariate Repeated Measurements","year":2007,"lang":"en","type":"article","venue":"Journal of Modern Applied Statistical Methods","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba; University of Alberta","funders":"","keywords":"Mathematics; Multivariate statistics; Statistics; Covariance; Multivariate analysis of variance; Kronecker product; Multivariate analysis; Sample size determination; Multivariate normal distribution; Analysis of covariance; Likelihood-ratio test; Repeated measures design; Econometrics; Kronecker delta","authors":[{"name":"Lisa M. Lix","is_ca":true},{"name":"Anita Lloyd","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3241192459659702,"gpt":0.5669658270404868,"spread":0.2428465810745166,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1259639,0.001727553,0.001839499,0.003999101,0.001243996,0.002470862,0.002897406,0.002151441,0.009123754],"category_scores_gemma":[0.3884489,0.001028619,0.002324609,0.004755926,0.002058223,0.003010436,0.00345004,0.003880095,0.002579207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001685751,"about_ca_system_score_gemma":0.005600689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001048274,"about_ca_topic_score_gemma":0.001311667,"domain_scores_codex":[0.8297886,0.1304932,0.008505543,0.005394156,0.02471629,0.001102158],"domain_scores_gemma":[0.6630323,0.2648067,0.01239138,0.02688249,0.03115369,0.0017334],"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":[0.005335463,0.001272675,0.005263937,0.003738004,0.001356352,0.0001990059,0.003448992,0.007286032,0.01137009,0.1325593,0.01800973,0.8101605],"study_design_scores_gemma":[0.005051772,0.0198151,0.1163731,0.008185548,0.003367751,0.004305305,0.004100717,0.1801974,0.0589312,0.3922407,0.2047601,0.002671247],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01397552,0.001987836,0.9729873,0.0003968129,0.0006266989,0.003858099,0.0007975447,0.001428151,0.003941966],"genre_scores_gemma":[0.02714157,0.001058042,0.9594454,0.000162934,0.00009043184,0.009947143,0.0004939451,0.0006896151,0.0009709122],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1259639,"threshold_uncertainty_score":0.6661687,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2103643033","doi":"","title":"Tw o-sample Hotelling's T 2 statistics based on the functional Mahalanobis semi-distance","year":2015,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Mahalanobis distance; Statistics; Mathematics; Principal component analysis; Context (archaeology); Covariance; Statistical distance; Sample (material); Multivariate normal distribution; Sample size determination; Multivariate statistics; Probability distribution; Geography","authors":[{"name":"Calle Madrid","is_ca":false},{"name":"Esdras Joseph","is_ca":false},{"name":"Pedro Galeano","is_ca":false},{"name":"Rosa E. Lillo","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.177050089396264,"gpt":0.4139089292700617,"spread":0.2368588398737976,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01181995,0.0008351953,0.001406943,0.002555798,0.0008594426,0.002044879,0.001686575,0.001295838,0.003285734],"category_scores_gemma":[0.06657755,0.0003749775,0.001854132,0.00257017,0.003561612,0.003848608,0.001865364,0.002694411,0.0006964218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001154251,"about_ca_system_score_gemma":0.001837114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002376113,"about_ca_topic_score_gemma":0.00167048,"domain_scores_codex":[0.9921441,0.004203184,0.0005597475,0.001205635,0.001595593,0.0002917375],"domain_scores_gemma":[0.9347796,0.05093909,0.002954532,0.0052342,0.005342446,0.0007501313],"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":[0.0008254214,0.0002773348,0.03685005,0.0009794086,0.0009525683,0.0009981535,0.001425311,0.1773611,0.007706063,0.5329655,0.007180978,0.2324782],"study_design_scores_gemma":[0.00005554872,0.000544997,0.01645004,0.0001228361,0.0000909789,0.0006310101,0.0005099791,0.707121,0.004022962,0.2645521,0.005734572,0.0001640292],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04542605,0.0004157271,0.9512665,0.0002157157,0.00009761439,0.0001115232,0.0003136682,0.0002257019,0.001927419],"genre_scores_gemma":[0.6742681,0.0006506613,0.319291,0.0003796925,0.0002263624,0.0008128075,0.001419005,0.0003172874,0.002635182],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01181995,"threshold_uncertainty_score":0.06251067,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2821990605","doi":"","title":"Statistiques. Concepts et applications Ed. 2","year":2010,"lang":"fr","type":"book","venue":"Presses de l'Université de Montréal PUM eBooks","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Humanities; Art; Philosophy","authors":[{"name":"Robert R. Haccoun","is_ca":false},{"name":"Denis Cousineau","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01955392119449823,"gpt":0.3028128531451802,"spread":0.283258931950682,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006202394,0.002012168,0.002446053,0.004921525,0.00142621,0.01035818,0.002927201,0.004500428,0.08092611],"category_scores_gemma":[0.01566555,0.001508477,0.002681907,0.008364986,0.005245386,0.008329218,0.003702103,0.008513352,0.04493399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00339588,"about_ca_system_score_gemma":0.004031553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002878312,"about_ca_topic_score_gemma":0.001244514,"domain_scores_codex":[0.9919665,0.002967753,0.0007798164,0.001549721,0.002443308,0.0002928766],"domain_scores_gemma":[0.9892833,0.007294792,0.0006542788,0.001409901,0.001117831,0.0002398916],"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":[0.00007241912,0.00006593949,0.0007872499,0.00247739,0.0001028323,0.0003212134,0.000854374,0.00169596,0.000726793,0.7305328,0.09681515,0.1655479],"study_design_scores_gemma":[0.00002682668,0.00003592403,0.0007638498,0.0011523,0.00003383832,0.0007471793,0.0003140327,0.002926916,0.0003964175,0.4924543,0.5011016,0.0000467282],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.00305618,0.1914576,0.4929658,0.02481808,0.01273128,0.0007093166,0.009921514,0.005233915,0.2591063],"genre_scores_gemma":[0.09399287,0.2092867,0.4272659,0.01801971,0.02048803,0.005407803,0.01480312,0.004125878,0.20661],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.08092611,"threshold_uncertainty_score":0.2707248,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1583582681","doi":"10.1111/j.1467-985x.2012.01045_8.x","title":"Multivariable Modeling and Multivariate Analysis for the Behavioral Sciences","year":2012,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Multivariable calculus; Multivariate statistics; Multivariate analysis; Mathematics; Computer science; Econometrics; Statistics; Engineering; Control engineering","authors":[{"name":"Chuck Chakrapani","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1255372416974175,"gpt":0.4225670179681305,"spread":0.2970297762707129,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02221109,0.002083252,0.004694318,0.003578168,0.001206423,0.004476446,0.002926677,0.00309188,0.00568951],"category_scores_gemma":[0.08648982,0.001236552,0.003100705,0.00654114,0.005041366,0.004228868,0.004095031,0.007649261,0.001226276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002379727,"about_ca_system_score_gemma":0.007097702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006778879,"about_ca_topic_score_gemma":0.006097039,"domain_scores_codex":[0.9766187,0.01906091,0.0009902235,0.001442315,0.00155341,0.0003344572],"domain_scores_gemma":[0.8921852,0.09438793,0.003614475,0.006797984,0.002280632,0.0007339029],"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":[0.00008990864,0.0001099568,0.002531918,0.0009522064,0.0007321755,0.0001893208,0.0004497392,0.01966572,0.0007221252,0.8413385,0.01226207,0.1209563],"study_design_scores_gemma":[0.0000316017,0.0000675905,0.001398633,0.000131843,0.0001197381,0.0001463877,0.00006092281,0.08924592,0.000207029,0.8963371,0.0122011,0.00005208301],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001554028,0.009221384,0.985379,0.002090533,0.000518135,0.000040417,0.0001549357,0.000259696,0.0007818581],"genre_scores_gemma":[0.1012109,0.01497071,0.8740841,0.001330478,0.003292675,0.000985547,0.000609158,0.0005361383,0.002980275],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02221109,"threshold_uncertainty_score":0.1174649,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3087396312","doi":"10.31235/osf.io/vxwqf","title":"Algorithmes d'apprentissage et modèles statistiques: Un exemple de régression régularisée et de validation croisée pour prédire le décrochage scolaire","year":2020,"lang":"fr","type":"article","venue":"","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Humanities; Physics; Political science; Philosophy","authors":[{"name":"Éric Lacourse","is_ca":false},{"name":"Véronique Dupéré","is_ca":false},{"name":"Charles‐Édouard Giguère","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0683547665586025,"gpt":0.3879040685138687,"spread":0.3195493019552662,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004357022,0.001344414,0.001313486,0.0009554952,0.0007779785,0.001512294,0.001518092,0.001402653,0.00296809],"category_scores_gemma":[0.009390092,0.0007204936,0.001269172,0.0009607985,0.001229095,0.000961157,0.001274904,0.00286906,0.001212165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009583292,"about_ca_system_score_gemma":0.002205311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02482678,"about_ca_topic_score_gemma":0.02737972,"domain_scores_codex":[0.9984622,0.0005865797,0.00009233718,0.0003419354,0.0003770302,0.0001398256],"domain_scores_gemma":[0.996197,0.002320192,0.0002437169,0.0005192332,0.0006400399,0.00007982619],"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":[0.0002688243,0.0001233691,0.006012553,0.000220402,0.0001673559,0.0002336263,0.0003691635,0.7479148,0.00761265,0.01303332,0.00300963,0.2210343],"study_design_scores_gemma":[0.00002318143,0.00006552011,0.001576786,0.00003788405,0.00002011752,0.00006090806,0.00005606792,0.9854785,0.003648643,0.005267086,0.003739274,0.00002597116],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03052369,0.0003723591,0.9654483,0.0003214795,0.00004117038,0.00007493268,0.0001914063,0.001909203,0.001117532],"genre_scores_gemma":[0.2570902,0.0005492718,0.7338607,0.0001811123,0.00005254127,0.0003919737,0.0007505529,0.0006326114,0.006491066],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02482678,"threshold_uncertainty_score":0.04936451,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4416524857","doi":"10.1016/b978-0-323-90509-1.00001-1","title":"Comparing groups using analysis of variance","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Analysis of variance; Mixed-design analysis of variance; Variance (accounting); One-way analysis of variance; Statistical analysis; Repeated measures design","authors":[{"name":"Janith Weeraman","is_ca":true},{"name":"Qingrun Zhang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1213381349052237,"gpt":0.3826724760448331,"spread":0.2613343411396095,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007106969,0.002540206,0.002573953,0.003901507,0.0005844388,0.002993518,0.002042701,0.001313276,0.05567828],"category_scores_gemma":[0.01901056,0.0008828877,0.001398032,0.003724445,0.001328512,0.002705814,0.001060541,0.002533518,0.02330501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005952655,"about_ca_system_score_gemma":0.000920346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008696943,"about_ca_topic_score_gemma":0.001311465,"domain_scores_codex":[0.9960667,0.001890373,0.0002857309,0.0005051653,0.001171001,0.00008108427],"domain_scores_gemma":[0.9836162,0.01379959,0.0003363968,0.0009836587,0.001153643,0.0001105277],"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":[0.0002112569,0.0001455025,0.000524097,0.001699454,0.0002277321,0.0001485202,0.0006751794,0.001772022,0.003520893,0.03682234,0.09941467,0.8548383],"study_design_scores_gemma":[0.000185537,0.0007766875,0.008542788,0.002244078,0.0005358083,0.001661032,0.001286153,0.02458781,0.007812029,0.2930728,0.6590433,0.0002518207],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002550223,0.01158109,0.9094554,0.001174246,0.003358481,0.0004497635,0.002119193,0.008298012,0.06101355],"genre_scores_gemma":[0.01355155,0.009802097,0.9166959,0.0005351352,0.0007492924,0.001722398,0.001951488,0.003204433,0.05178772],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05567828,"threshold_uncertainty_score":0.1862624,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6931774150","doi":"10.5683/sp3/lz8azu","title":"Lake Snow depth observations derived from Ground Penetrating Radar for four lakes near Yellowknife, Northwest Territories","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Snow; Ground-penetrating radar; Radar; Water equivalent; Weighting; Snow cover; Lidar","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.1257348765032815,"gpt":0.3560695189432746,"spread":0.2303346424399931,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004338337,0.0008527117,0.0006080802,0.001594206,0.0006120734,0.0007602275,0.001069192,0.0005060626,0.008343248],"category_scores_gemma":[0.001255763,0.0003630413,0.0005374595,0.003469109,0.0002550847,0.0004741832,0.000922004,0.0006067829,0.008902838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001228411,"about_ca_system_score_gemma":0.002107953,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1626542,"about_ca_topic_score_gemma":0.2936395,"domain_scores_codex":[0.9996978,0.00002469474,0.00002699185,0.00009365924,0.00009199481,0.00006490495],"domain_scores_gemma":[0.9992433,0.00009273906,0.00009119486,0.0001397265,0.0003492537,0.00008380658],"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":[0.0001869668,0.0001123708,0.03057765,0.0007219213,0.0001170416,0.0001769385,0.0002933854,0.002547026,0.0009526205,0.0006949257,0.9467025,0.01691657],"study_design_scores_gemma":[0.0001851863,0.00003339585,0.1674512,0.0002725593,0.00005336159,0.0001045893,0.000752842,0.002850021,0.001338241,0.0005813173,0.8263222,0.00005511866],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.005014895,0.00003877268,0.0001326229,0.00003385209,0.00001282137,0.00001550071,0.9938256,0.0001501886,0.0007758532],"genre_scores_gemma":[0.002730804,0.00003172099,0.0003507092,0.000008744495,0.000002783327,0.00005982575,0.9959228,0.00002849059,0.0008640736],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8373458,"threshold_uncertainty_score":0.3234149,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3032053659","doi":"10.52041/srap.03313","title":"St@tNet: an assessment and new developments","year":2003,"lang":"en","type":"preprint","venue":"","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Glossary; The Internet; Computer science; Distance education; World Wide Web; Multimedia; Mathematics education; Mathematics","authors":[{"name":"Gilbert Saporta","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3470421453198535,"gpt":0.5550750835621723,"spread":0.2080329382423188,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01742793,0.00120941,0.0008474402,0.00444831,0.001825523,0.01623345,0.003390425,0.00307887,0.09705253],"category_scores_gemma":[0.02855489,0.0005441513,0.001120966,0.006505718,0.001168695,0.01137233,0.007651346,0.004109888,0.06399048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007159771,"about_ca_system_score_gemma":0.01729462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007942234,"about_ca_topic_score_gemma":0.0103837,"domain_scores_codex":[0.9843538,0.00335483,0.0007754075,0.0009516796,0.00928051,0.001283796],"domain_scores_gemma":[0.9722057,0.001939779,0.00055533,0.001332789,0.01423433,0.009732014],"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":[0.0001237192,0.0002840728,0.0007590543,0.0003533462,0.000006311409,0.0001401938,0.0007809659,0.0004567771,0.0004953448,0.01439609,0.6231248,0.3590793],"study_design_scores_gemma":[0.0000108034,0.00007030852,0.0009635521,0.0003518637,0.000003063362,0.0001062345,0.000369406,0.0003366741,0.000182395,0.001790929,0.9958021,0.00001273577],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.02319635,0.0319388,0.03767939,0.1400361,0.04472988,0.0009918578,0.01065271,0.01172531,0.6990496],"genre_scores_gemma":[0.06219903,0.04065534,0.06588914,0.01148681,0.007692094,0.001061909,0.02747311,0.008088206,0.7754544],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.09705253,"threshold_uncertainty_score":0.3246731,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6929697210","doi":"10.5061/dryad.tx95x69w7","title":"Life‐stage‐dependent supergene haplotype frequencies and metapopulation neutral genetic patterns of Atlantic cod, Gadus morhua, from Canada's Northern cod stock region and adjacent areas","year":2021,"lang":"en","type":"dataset","venue":"Open MIND","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Gadus; Atlantic cod; Bay; Carpentaria; Stock (firearms); Habitat; Metapopulation; Population; Gadidae; Population genetics","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.1160496689503408,"gpt":0.3460928103631404,"spread":0.2300431414127996,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006667693,0.0003574396,0.0004743856,0.001054201,0.0005924575,0.0006813925,0.001026378,0.0004352985,0.00478992],"category_scores_gemma":[0.00263055,0.000256565,0.0003351775,0.002021247,0.000285772,0.0002371312,0.0006050703,0.0005321215,0.00176407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001596738,"about_ca_system_score_gemma":0.001870156,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4493974,"about_ca_topic_score_gemma":0.6359894,"domain_scores_codex":[0.9997032,0.00003021637,0.0000238684,0.0001337426,0.00004339781,0.00006560078],"domain_scores_gemma":[0.9990318,0.0002744131,0.000148057,0.0001628509,0.0002798956,0.0001030739],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008916918,0.0001469973,0.5107761,0.001311589,0.0006451056,0.000316796,0.0009831912,0.003834658,0.001952576,0.001468503,0.4484612,0.02921164],"study_design_scores_gemma":[0.0002199412,0.00003085087,0.9236592,0.0002042747,0.0001481414,0.000168217,0.0004597222,0.001828176,0.0003393811,0.0003777454,0.07252815,0.0000362059],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.08488075,0.0001850473,0.0003056055,0.00008813364,0.00001343622,0.00002053221,0.9135951,0.0001027876,0.0008085582],"genre_scores_gemma":[0.05378814,0.00008525309,0.0007484924,0.00003538031,0.000004217701,0.00008678926,0.9441718,0.0000326129,0.001047218],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5506026,"threshold_uncertainty_score":0.8935632,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2119329932","doi":"10.1111/j.1096-0031.2003.tb00389.x","title":"Probabilities for completely pectinate and symmetric cladograms","year":2003,"lang":"en","type":"article","venue":"Cladistics","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Biology; Biological system; Mathematics","authors":[{"name":"Jon R. Stone","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2078487083253998,"gpt":0.4176686548198946,"spread":0.2098199464944947,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007320966,0.0008012364,0.0009411267,0.005179499,0.001765693,0.00385863,0.002887496,0.001515606,0.011225],"category_scores_gemma":[0.07878041,0.001132389,0.001426166,0.002621993,0.002186004,0.005582387,0.003591607,0.002636779,0.002499938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001863863,"about_ca_system_score_gemma":0.001434257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007183186,"about_ca_topic_score_gemma":0.001451192,"domain_scores_codex":[0.9948761,0.001254797,0.0006241585,0.0009503014,0.002024321,0.0002703437],"domain_scores_gemma":[0.9489748,0.0428903,0.0018588,0.002874825,0.002811277,0.000589981],"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":[0.000359061,0.00009652681,0.009649633,0.0008512691,0.0001356935,0.0007078656,0.0007398946,0.1167042,0.008197071,0.4810183,0.01245281,0.3690877],"study_design_scores_gemma":[0.00003838082,0.00003950327,0.002504178,0.0001758514,0.00005406383,0.0007161641,0.0001309666,0.364035,0.008366015,0.6175756,0.006275128,0.00008891595],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01254347,0.0002230093,0.9833804,0.0001301134,0.00008082488,0.0001350815,0.0004267623,0.0008563415,0.002224068],"genre_scores_gemma":[0.1413468,0.000377426,0.8530402,0.0001132386,0.0001360745,0.0006689662,0.001346417,0.0008715551,0.002099384],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.011225,"threshold_uncertainty_score":0.03871745,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1922240578","doi":"10.11144/javeriana.sc17-2.pamc","title":"p &lt; 0,05, ¿Criterio mágico para resolver cualquier problema o leyenda urbana?","year":2012,"lang":"en","type":"article","venue":"Universitas Scientiarum","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Null hypothesis; p-value; Statistical hypothesis testing; Type I and type II errors; Bayesian probability; Value (mathematics); Statistics; Alternative hypothesis; Mathematics; Statistical analysis; Econometrics","authors":[{"name":"Pedro Monterrey Gutiérrez Monterrey Gutiérrez","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1027963930569019,"gpt":0.3594203116049088,"spread":0.256623918548007,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.05241415,0.0009714646,0.001928525,0.002672419,0.001967719,0.007223519,0.003828148,0.005189272,0.03500286],"category_scores_gemma":[0.3218643,0.0005621189,0.001413919,0.005225028,0.009467711,0.005296104,0.00331634,0.007269974,0.007050497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002726547,"about_ca_system_score_gemma":0.007799414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002456096,"about_ca_topic_score_gemma":0.001664458,"domain_scores_codex":[0.9339458,0.03904366,0.004400086,0.007811175,0.0129585,0.001840799],"domain_scores_gemma":[0.7164157,0.2354809,0.01337168,0.01001,0.01958052,0.005141222],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.003935037,0.0004576554,0.04029977,0.01175658,0.001151467,0.001973717,0.004471505,0.002799395,0.002639806,0.2452226,0.3151509,0.3701416],"study_design_scores_gemma":[0.0005746094,0.001810357,0.05237594,0.007551571,0.0007614858,0.001994262,0.007754117,0.0146057,0.005567978,0.3112256,0.5955327,0.0002455873],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.07930523,0.03757141,0.3309197,0.1839773,0.03962419,0.004749063,0.01630464,0.003734334,0.3038141],"genre_scores_gemma":[0.6432131,0.0053309,0.2765327,0.02851833,0.004536436,0.009713227,0.002346254,0.001708486,0.0281006],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.9475859,"threshold_uncertainty_score":0.2771958,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2496104205","doi":"10.2495/dne-v11-n3-258-267","title":"Reducing test time for selective populations in semiconductor manufacturing","year":2016,"lang":"en","type":"article","venue":"International Journal of Design & Nature and Ecodynamics","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Semiconductor device fabrication; Test (biology); Engineering; Manufacturing engineering; Electrical engineering; Biology; Ecology","authors":[{"name":"Dana Ann Park","is_ca":false},{"name":"M. Schuldenfrei","is_ca":false},{"name":"Gal Levy","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05539578732856539,"gpt":0.3744688774968079,"spread":0.3190730901682425,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01247345,0.001062352,0.001494939,0.002873904,0.001787319,0.002161621,0.004592316,0.001704059,0.01292398],"category_scores_gemma":[0.07449131,0.0007968454,0.001230488,0.001401074,0.001968948,0.003272928,0.005253016,0.002433541,0.004324575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002220858,"about_ca_system_score_gemma":0.004089831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003585399,"about_ca_topic_score_gemma":0.004239586,"domain_scores_codex":[0.9866406,0.0049889,0.0005654844,0.002009276,0.004784706,0.001011064],"domain_scores_gemma":[0.9171868,0.04926302,0.005685727,0.0118476,0.01260825,0.003408625],"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":[0.002020846,0.001453005,0.05292389,0.0005583108,0.0002107381,0.001473645,0.002347033,0.04892247,0.0221307,0.0367009,0.02414538,0.8071131],"study_design_scores_gemma":[0.00110823,0.009189356,0.05573324,0.0007129538,0.000547595,0.005030708,0.006985312,0.5491747,0.08235707,0.1727166,0.1160301,0.0004140842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1997192,0.00313557,0.7484298,0.006907718,0.001247489,0.001645992,0.0005974985,0.01107699,0.02723963],"genre_scores_gemma":[0.7486905,0.0009257624,0.2354517,0.002194276,0.0003316315,0.001565446,0.0008700226,0.0008673359,0.009103335],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01292398,"threshold_uncertainty_score":0.06596667,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6929590342","doi":"10.5061/dryad.0k6djhb90","title":"Land-use legacies affect flower visitation network structure after forest restoration","year":2024,"lang":"en","type":"dataset","venue":"DRYAD","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":1,"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":"U.S. Department of Energy","keywords":"Understory; Restoration ecology; Agriculture; Nestedness; Agricultural land; Forest restoration; Canopy","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.0431827892719495,"gpt":0.3761157628939055,"spread":0.332932973621956,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009168708,0.0005569062,0.000630396,0.001049963,0.0005745419,0.0009778739,0.001430109,0.0007331832,0.01146086],"category_scores_gemma":[0.003492867,0.0002585309,0.0007655837,0.001483958,0.0002996652,0.0004752709,0.001109321,0.0008909982,0.0064673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008713562,"about_ca_system_score_gemma":0.0006724589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03424807,"about_ca_topic_score_gemma":0.08691407,"domain_scores_codex":[0.9996247,0.00008992113,0.00003749171,0.0001261858,0.00004991642,0.00007166786],"domain_scores_gemma":[0.9991013,0.0003444068,0.0001585502,0.0001573342,0.0001409413,0.00009752851],"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":[0.001020607,0.0003097528,0.111581,0.001775741,0.0004121864,0.0002870698,0.0004878889,0.004070924,0.001156664,0.002172319,0.8595744,0.01715143],"study_design_scores_gemma":[0.00132194,0.0001837303,0.3893809,0.0005926048,0.0002830492,0.0005666362,0.001258151,0.009312612,0.001165683,0.002523204,0.5932911,0.0001203373],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02226373,0.0002351412,0.0002657921,0.000257731,0.00004868902,0.00002369415,0.9755657,0.0002804961,0.001059161],"genre_scores_gemma":[0.02292981,0.00009035431,0.0009738302,0.00008761701,0.0000109967,0.0001440084,0.9744528,0.00005495952,0.001255678],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03424807,"threshold_uncertainty_score":0.06809741,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6929005679","doi":"10.4224/16606877","title":"Validation de la prédiction des épaisseurs de différents types de bouteilles pour le procédé d'étirage soufflage de la compagnie Husky à l'aide du logiciel BlowSim","year":2010,"lang":"fr","type":"report","venue":"NPARC","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Work (physics); Context (archaeology); Data collection; Software","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.07359504450568856,"gpt":0.3722239185869652,"spread":0.2986288740812767,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00438134,0.001069969,0.0007477176,0.001417696,0.0005283356,0.001008708,0.001202016,0.001642546,0.002769519],"category_scores_gemma":[0.01238696,0.0003607637,0.0009925251,0.00056738,0.0006586905,0.001367974,0.0007038816,0.0008787329,0.001000152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008507769,"about_ca_system_score_gemma":0.001278425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01546299,"about_ca_topic_score_gemma":0.0106373,"domain_scores_codex":[0.9982502,0.0005654786,0.0001062988,0.0004434723,0.0004600269,0.0001744742],"domain_scores_gemma":[0.9891806,0.007225637,0.0005609982,0.001037712,0.001776102,0.0002189722],"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":[0.002721398,0.0005280554,0.1038252,0.0002650376,0.0004461069,0.0001710897,0.0002665062,0.6699644,0.0413648,0.002433065,0.001817183,0.1761973],"study_design_scores_gemma":[0.00003294021,0.0001770395,0.02515434,0.00001310655,0.00002845967,0.00005385832,0.00004982283,0.9454254,0.02805949,0.0004894066,0.0004873745,0.00002881921],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8525447,0.0002185451,0.1440428,0.000106527,0.00006216718,0.00005766542,0.0005555191,0.001353764,0.001058371],"genre_scores_gemma":[0.9639595,0.00004703207,0.033002,0.00002390132,0.00001123289,0.00005174515,0.0007294053,0.00008216209,0.002092937],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01546299,"threshold_uncertainty_score":0.03074598,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6925660437","doi":"10.20381/ruor-26840","title":"Migration, Refugees and Conceptualizing Canadian Identity: The Syrian Refugee Crisis and the Discursivity of Canadian Politics.","year":2021,"lang":"en","type":"other","venue":"uO Research (University of Ottawa)","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Refugee; Refugee crisis; Syrian refugees; Government (linguistics); Immigration; Asylum seeker","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.1025101349706202,"gpt":0.3914265988106737,"spread":0.2889164638400535,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004889926,0.000541686,0.000555513,0.003457523,0.02779266,0.01127879,0.001641454,0.002169037,0.01183745],"category_scores_gemma":[0.01698522,0.0002355047,0.0002710732,0.01015442,0.02253652,0.004530762,0.005909007,0.002809221,0.0004619937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07070556,"about_ca_system_score_gemma":0.1636092,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9917854,"about_ca_topic_score_gemma":0.9962166,"domain_scores_codex":[0.9976193,0.0007892987,0.00006518879,0.0001474648,0.0006422675,0.0007364156],"domain_scores_gemma":[0.9937373,0.002048102,0.0003383556,0.0002657568,0.001905591,0.001704885],"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":[0.00009063769,0.00003685445,0.01995272,0.0002450571,0.00002869601,0.0003121856,0.2956796,0.000371147,0.0001031865,0.409636,0.1917212,0.08182273],"study_design_scores_gemma":[0.00001406553,0.00001261051,0.03393127,0.001247981,0.00004134413,0.0001631727,0.5843963,0.0004640085,0.0001041082,0.04700763,0.332492,0.000125555],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.1956312,0.09298165,0.002250992,0.3980403,0.002354281,0.00008587941,0.00270574,0.0001232687,0.3058266],"genre_scores_gemma":[0.9271769,0.03211109,0.001713091,0.009757597,0.0002900002,0.00005102539,0.0004958876,0.0001045111,0.0282998],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.07070556,"threshold_uncertainty_score":0.5130071,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6929137109","doi":"10.48336/gmq5-q483","title":"Modeling magnetic nanoparticles: application to hyperthermia","year":2022,"lang":"en","type":"article","venue":"Memorial University Research Repository (Memorial University)","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":0,"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":"Scaling; Magnetization; Micromagnetics; Nanoparticle; Magnetic hysteresis; Magnetic nanoparticles; Magnetic field; Hysteresis","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.07715490016648258,"gpt":0.3313427926672352,"spread":0.2541878925007526,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002979107,0.0003428787,0.0003880023,0.0003097039,0.0003399364,0.0004285216,0.0006595646,0.001031491,0.0006803277],"category_scores_gemma":[0.001314515,0.0002057779,0.0003560036,0.0003370671,0.0004508576,0.0004108701,0.0004677461,0.0003166883,0.0001451246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006292867,"about_ca_system_score_gemma":0.000736137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004399526,"about_ca_topic_score_gemma":0.002834276,"domain_scores_codex":[0.9998873,0.00004916126,0.000004464108,0.00001368381,0.00003144656,0.00001394036],"domain_scores_gemma":[0.999663,0.0002120472,0.00004392185,0.00002296785,0.0000347306,0.00002329508],"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":[0.00001084493,0.00002159275,0.0004966346,0.00002859903,0.00001022148,0.00003857166,0.00004302909,0.979413,0.004480524,0.01294692,0.000193286,0.002316763],"study_design_scores_gemma":[0.000003364584,0.000006516496,0.0000644892,0.000001831263,0.000001449417,0.000005349864,0.000003663314,0.9966772,0.0003777728,0.002495728,0.0003605816,0.000002039781],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3047558,0.0007996963,0.6772307,0.00138416,0.0001144624,0.0001486721,0.0002162185,0.0006914883,0.01465884],"genre_scores_gemma":[0.8713134,0.000490002,0.1246881,0.0001563968,0.00004668846,0.0003272419,0.0001096132,0.000158453,0.002710161],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004399526,"threshold_uncertainty_score":0.008747876,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6931569918","doi":"10.5281/zenodo.8083005","title":"cheshmi/sc23-ad-sparse-fusion: v1.0.1","year":2023,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto; McMaster University","funders":"","keywords":"Property (philosophy); Product (mathematics); Set (abstract data type); Sensor fusion","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.143250470265544,"gpt":0.3549702304002009,"spread":0.2117197601346568,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00390548,0.002451073,0.001598679,0.001969467,0.0009466995,0.002950042,0.003277467,0.003323737,0.1980971],"category_scores_gemma":[0.008641898,0.0008393571,0.001313201,0.001775608,0.001041764,0.002532696,0.003913729,0.002961812,0.1618776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001959396,"about_ca_system_score_gemma":0.002083122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005966021,"about_ca_topic_score_gemma":0.006472863,"domain_scores_codex":[0.9973616,0.000584357,0.00009385835,0.0003033627,0.001394072,0.0002628173],"domain_scores_gemma":[0.9972553,0.0006931227,0.0001396377,0.0009002608,0.00076143,0.0002502062],"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":[0.0003909386,0.00009194297,0.0003144862,0.0003867741,0.0001166515,0.0001498726,0.00006612766,0.01165483,0.004376587,0.05687339,0.8468917,0.07868664],"study_design_scores_gemma":[0.000598012,0.0001862645,0.00065667,0.0001946992,0.00005676063,0.0004468523,0.00004943051,0.1969058,0.02016815,0.1301446,0.6504315,0.0001612168],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.004197211,0.001699093,0.5410348,0.003542154,0.002763758,0.0007732586,0.06261317,0.1614819,0.2218947],"genre_scores_gemma":[0.08952534,0.001596483,0.5256228,0.002659072,0.00171963,0.001666304,0.1336617,0.09398858,0.14956],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.1980971,"threshold_uncertainty_score":0.6627008,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6932185033","doi":"10.5683/sp3/lqidlu","title":"Survey on Early Learning and Child Care Arrangements, 2019 [Canada]","year":2019,"lang":"en","type":"dataset","venue":"Borealis","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Statistics Canada","funders":"","keywords":"Child care; Pandemic; Face (sociological concept); Data collection; Cover (algebra); Child development","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.05705752650113757,"gpt":0.3621611435087362,"spread":0.3051036170075986,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002034227,0.001366874,0.001310047,0.003522428,0.002114913,0.002413277,0.003434348,0.001121993,0.01804709],"category_scores_gemma":[0.01368706,0.0007265332,0.001162708,0.01230553,0.0005033195,0.0009687297,0.001693336,0.002203058,0.01349488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01786771,"about_ca_system_score_gemma":0.0336543,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9620919,"about_ca_topic_score_gemma":0.9786345,"domain_scores_codex":[0.9981806,0.0001743356,0.0002562189,0.0002651124,0.0007307188,0.0003930179],"domain_scores_gemma":[0.9885288,0.0007526518,0.000733408,0.0006536025,0.008153915,0.001177559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0000717591,0.00002144662,0.008017576,0.000268332,0.00003635589,0.0000185321,0.00003528425,0.0001180827,0.00002089733,0.0003251283,0.9887922,0.002274325],"study_design_scores_gemma":[0.0005111994,0.00004038341,0.2623163,0.0007997471,0.0001018084,0.00010699,0.0005949658,0.0009756471,0.0002794489,0.0007076199,0.733459,0.0001067603],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003206114,0.00005946301,0.00002841995,0.0001028194,0.00001458945,0.00001866495,0.9989228,0.0000419897,0.0004906618],"genre_scores_gemma":[0.001636853,0.0001401711,0.000244013,0.0001106634,0.000009458424,0.0001248302,0.9964119,0.00002383887,0.001298344],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03790814,"threshold_uncertainty_score":0.1296399,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}