{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":23,"total_is_capped":false,"direct_labels_cover":1,"predictions_cover":23,"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":"4243585afc1b","filters":{"venue":"Journal of Educational and Behavioral Statistics"}},"results":[{"id":"W1999688181","doi":"10.3102/10769986027003291","title":"Nonparametric Item Response Function Estimates with the EM Algorithm","year":2002,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Advanced Statistical Modeling Techniques","field":"Computer Science","cited_by":83,"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":"Nonparametric statistics; Mathematics; Item response theory; Functional data analysis; Differential item functioning; Algorithm; Latent variable; Latent variable model; Smoothness; Statistics; Function (biology); Mathematical optimization; Psychometrics","authors":[{"name":"Natasha Rossi","is_ca":true},{"name":"Xiaohui Wang","is_ca":false},{"name":"J. O. Ramsay","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04016072169252984,"gpt":0.3276923298278803,"spread":0.2875316081353504,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0195016,0.001749702,0.003603788,0.003115173,0.001071007,0.002250154,0.005791405,0.003023797,0.01204697],"category_scores_gemma":[0.06602999,0.001739831,0.002814284,0.004551479,0.001348141,0.003120689,0.003669928,0.004711271,0.005739548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001334877,"about_ca_system_score_gemma":0.00253054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002890076,"about_ca_topic_score_gemma":0.002812695,"domain_scores_codex":[0.9870651,0.01007004,0.0004859319,0.001050742,0.001102591,0.0002256853],"domain_scores_gemma":[0.9793208,0.015461,0.0006535429,0.002451612,0.001959237,0.0001539479],"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":[0.0004337094,0.0002454355,0.002016139,0.0004551423,0.0006036349,0.0001370349,0.0004207295,0.2762919,0.001052063,0.09867163,0.0142847,0.6053879],"study_design_scores_gemma":[0.0001331325,0.00008507619,0.001139824,0.000103863,0.00007930942,0.0001432622,0.00008607872,0.856423,0.001194907,0.131535,0.009004856,0.00007155325],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001066949,0.0001070813,0.9975217,0.00009190221,0.00001405636,0.000130514,0.00009611431,0.0004930967,0.0004784933],"genre_scores_gemma":[0.02199253,0.0001258413,0.9745598,0.0001039898,0.00003294263,0.00113678,0.0005505414,0.0002542898,0.001243324],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0195016,"threshold_uncertainty_score":0.1031355,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2163829751","doi":"10.3102/1076998607307355","title":"Causal Inference for Time-Varying Instructional Treatments","year":2008,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"School Choice and Performance","field":"Social Sciences","cited_by":76,"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":"Causal inference; Endogeneity; Weighting; Mathematics education; Value (mathematics); Inverse probability weighting; Multilevel model; Causal model; Econometrics; Inference; Outcome (game theory); Average treatment effect; Academic achievement; Computer science; Psychology; Propensity score matching; Statistics; Mathematics; Machine learning; Medicine; Artificial intelligence","authors":[{"name":"Guanglei Hong","is_ca":true},{"name":"Stephen W. Raudenbush","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08936654137525234,"gpt":0.4135590799087178,"spread":0.3241925385334655,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1611749,0.002265797,0.005090001,0.006160993,0.003240641,0.005192946,0.007568586,0.006844993,0.01879952],"category_scores_gemma":[0.4561103,0.002651281,0.008715903,0.005676628,0.008048142,0.008796516,0.007417229,0.01159116,0.0009433019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005432348,"about_ca_system_score_gemma":0.005233943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01279165,"about_ca_topic_score_gemma":0.008609131,"domain_scores_codex":[0.8490179,0.1186766,0.004138808,0.01583271,0.009528828,0.002805141],"domain_scores_gemma":[0.2989704,0.6427408,0.01828815,0.03437829,0.004344279,0.001278139],"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":[0.0007705242,0.0008460152,0.0203941,0.0007087095,0.004217661,0.0007455058,0.001512089,0.03763174,0.0003892902,0.8606992,0.003128238,0.06895687],"study_design_scores_gemma":[0.0005887452,0.0003070641,0.003766439,0.0001835148,0.001214823,0.0001708438,0.0003223791,0.147049,0.0007898217,0.8415756,0.003939868,0.00009178651],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0152714,0.0006198671,0.9755401,0.002974385,0.0003503535,0.0008834467,0.0004293776,0.0003470318,0.003584035],"genre_scores_gemma":[0.5496599,0.001221367,0.4304256,0.002881979,0.0007323166,0.005996626,0.000924338,0.0001431437,0.008014728],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8388251,"threshold_uncertainty_score":0.8523844,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2033872871","doi":"10.3102/1076998613481500","title":"A Two-Decision Model for Responses to Likert-Type Items","year":2013,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":75,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Kronos (Canada)","funders":"","keywords":"Likert scale; Item response theory; Set (abstract data type); Decision model; Econometrics; Functional response; Model selection; Response time; Statistics; Computer science; Mathematics; Machine learning; Psychometrics","authors":[{"name":"Anne Thissen-Roe","is_ca":true},{"name":"David Thissen","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.5866905625763341,"gpt":0.5681326453150991,"spread":0.01855791726123501,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.07903546,0.004036615,0.004084625,0.003727707,0.001831373,0.005916993,0.01031211,0.005959656,0.03511814],"category_scores_gemma":[0.1068445,0.002158147,0.005476612,0.004253098,0.003726714,0.006336994,0.003146931,0.007896593,0.01406138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004472696,"about_ca_system_score_gemma":0.003724764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005502418,"about_ca_topic_score_gemma":0.004700806,"domain_scores_codex":[0.9280175,0.05193562,0.003245433,0.008397638,0.005969572,0.002434303],"domain_scores_gemma":[0.9165291,0.06440748,0.005172437,0.007051762,0.005693797,0.001145465],"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":[0.004754398,0.002777515,0.03104302,0.00133365,0.001193611,0.001068766,0.005061826,0.1824602,0.002387007,0.5967607,0.01738459,0.1537747],"study_design_scores_gemma":[0.0008317665,0.001269007,0.005186636,0.0001577218,0.0002190762,0.000509973,0.0004739285,0.7621812,0.0007436874,0.2168553,0.01132793,0.0002436736],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04223395,0.0002517975,0.9370919,0.001951747,0.0004259215,0.005174892,0.002832417,0.001165007,0.008872296],"genre_scores_gemma":[0.4567814,0.0006536965,0.4796817,0.001325914,0.0003850942,0.01932652,0.004809695,0.0003496355,0.03668652],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07903546,"threshold_uncertainty_score":0.4179845,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2133414959","doi":"10.3102/10769986027001031","title":"Visions and Re-Visions of Charles Joseph Minard","year":2002,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":75,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Vision; Depiction; Graphics; Visualization; Computer science; Thematic map; Data science; Computer graphics (images); Visual arts; Cartography; Artificial intelligence; Sociology; Art; Geography","authors":[{"name":"Michael Friendly","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06888977604375794,"gpt":0.3729042043720761,"spread":0.3040144283283181,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00777889,0.0005446761,0.0004914824,0.00192035,0.003717346,0.01089334,0.0009921272,0.002691703,0.002084845],"category_scores_gemma":[0.01788588,0.0004456254,0.0003062235,0.001518183,0.02033538,0.008637617,0.002681885,0.01079682,0.0009145509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00473434,"about_ca_system_score_gemma":0.003162747,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01526597,"about_ca_topic_score_gemma":0.01040251,"domain_scores_codex":[0.9927994,0.003636511,0.0001618032,0.001003903,0.002115761,0.0002826269],"domain_scores_gemma":[0.9892046,0.004802285,0.0002914868,0.0006749217,0.003540999,0.001485757],"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":[0.0000713831,0.00003170006,0.001055093,0.000106488,0.00001809551,0.0001684892,0.01528203,0.0006028122,0.0005962305,0.6643404,0.2611351,0.05659218],"study_design_scores_gemma":[0.000006308318,0.00001861481,0.0004479776,0.000117232,0.00000526943,0.0002350068,0.003049036,0.0006395676,0.0004850475,0.08290281,0.9120478,0.0000453059],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02423885,0.08399288,0.04318915,0.7449782,0.01913307,0.00004004272,0.0001085151,0.0005930976,0.08372623],"genre_scores_gemma":[0.5898284,0.07514531,0.04078512,0.1468899,0.0173458,0.0001322253,0.000154103,0.001701206,0.128018],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01526597,"threshold_uncertainty_score":0.04113925,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2158157835","doi":"10.3102/10769986027002105","title":"Constrained Principal Component Analysis: Various Applications","year":2002,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Sensory Analysis and Statistical Methods","field":"Agricultural and Biological Sciences","cited_by":62,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"","keywords":"Principal component analysis; Contingency table; Set (abstract data type); Computer science; Multivariate statistics; Reliability (semiconductor); Component (thermodynamics); Regression analysis; Variety (cybernetics); Statistics; Data mining; Econometrics; Mathematics; Machine learning","authors":[{"name":"Michael A. Hunter","is_ca":true},{"name":"Yoshio Takane","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08203732621707842,"gpt":0.3446977867055444,"spread":0.2626604604884659,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009481243,0.002274972,0.001942696,0.005548128,0.001360742,0.003312462,0.001887077,0.002198882,0.006600094],"category_scores_gemma":[0.0363216,0.001051647,0.00215335,0.01418569,0.002616013,0.002752927,0.00275961,0.003035407,0.002612615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001170455,"about_ca_system_score_gemma":0.002352939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004585182,"about_ca_topic_score_gemma":0.003816521,"domain_scores_codex":[0.992681,0.003639058,0.0004668061,0.001071382,0.001987218,0.0001544911],"domain_scores_gemma":[0.9843008,0.0105587,0.0006871392,0.001591935,0.00258437,0.000277141],"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":[0.0001053122,0.0001145981,0.003751042,0.001214384,0.0005227643,0.0002781933,0.0009013471,0.0207899,0.001685767,0.1997559,0.02145492,0.7494259],"study_design_scores_gemma":[0.00006702314,0.00009704051,0.008079606,0.0009209872,0.0001873493,0.0007823952,0.0005961031,0.1359622,0.002890806,0.6949024,0.1552554,0.0002587223],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004347945,0.01847676,0.9604444,0.00218423,0.0003493733,0.0003292279,0.0005405372,0.001071044,0.01225642],"genre_scores_gemma":[0.07766788,0.02466241,0.888955,0.0005629061,0.0008259509,0.0008835557,0.0007666175,0.0006162632,0.005059389],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009481243,"threshold_uncertainty_score":0.05014217,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2097672163","doi":"10.3102/1076998610396894","title":"A Didactic Presentation of Snijders’s <i> l <sub>z</sub> * </i> Index of Person Fit With Emphasis on Response Model Selection and Ability Estimation","year":2011,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":52,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Ambiguity; Estimator; Item response theory; Index (typography); Generalization; Statistics; Set (abstract data type); Mathematics; Sample (material); Computer science; Type (biology); Psychology; Artificial intelligence; Psychometrics","authors":[{"name":"David Magis","is_ca":false},{"name":"Gilles Raîche","is_ca":true},{"name":"Sébastien Béland","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.4831390672638221,"gpt":0.4779579214191477,"spread":0.00518114584467444,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002852819,0.001905477,0.0009796853,0.00244447,0.0005872955,0.001742415,0.001130728,0.001616551,0.09426639],"category_scores_gemma":[0.0110971,0.0004713817,0.0009681942,0.001871974,0.0009877152,0.002280837,0.001793616,0.003569924,0.03403534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00113978,"about_ca_system_score_gemma":0.0007098341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008216156,"about_ca_topic_score_gemma":0.00108764,"domain_scores_codex":[0.9990379,0.0004347351,0.00008385306,0.0001039923,0.0002673994,0.00007216841],"domain_scores_gemma":[0.9956008,0.003136874,0.0001577116,0.0001835543,0.0007301862,0.0001908938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000858095,0.0001284357,0.0003510203,0.0004286684,0.00001437984,0.0002572882,0.0002927021,0.001128392,0.002400011,0.02847487,0.8064011,0.1600375],"study_design_scores_gemma":[0.00004893293,0.0002366324,0.001660473,0.0004080913,0.00001069846,0.0009329488,0.0002716269,0.003925194,0.00189221,0.0435411,0.946999,0.00007305219],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006436783,0.01570272,0.7301543,0.03648999,0.04441789,0.00209003,0.005932337,0.007146413,0.1516296],"genre_scores_gemma":[0.05762472,0.02165396,0.5773421,0.02641121,0.02726313,0.004648178,0.007135786,0.00539857,0.2725224],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.09426639,"threshold_uncertainty_score":0.3153525,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2071849850","doi":"10.3102/1076998609332756","title":"Sample Size Estimation in Cluster Randomized Educational Trials: An Empirical Bayes Approach","year":2009,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":30,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Intraclass correlation; Bayes' theorem; Computer science; Cluster (spacecraft); Statistics; Sample size determination; Estimation; Sample (material); Data mining; Task (project management); Field (mathematics); Econometrics; Bayesian probability; Mathematics; Artificial intelligence; Psychometrics","authors":[{"name":"Michael Rotondi","is_ca":true},{"name":"Allan Donner","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1729810713784575,"gpt":0.5008700679701498,"spread":0.3278889965916923,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2323861,0.002486333,0.00945213,0.005913597,0.00135379,0.003259601,0.006612604,0.005829132,0.004191216],"category_scores_gemma":[0.4642672,0.002101685,0.004328791,0.004186567,0.004222088,0.003808479,0.003097125,0.007025414,0.0008724232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002558714,"about_ca_system_score_gemma":0.005226885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002765544,"about_ca_topic_score_gemma":0.002156398,"domain_scores_codex":[0.7071114,0.2725939,0.006104433,0.006005429,0.007532097,0.0006527388],"domain_scores_gemma":[0.4853451,0.490923,0.006569588,0.01156225,0.004773323,0.0008268286],"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":[0.005051261,0.0006249609,0.005051394,0.00515365,0.005032888,0.0004529592,0.001352862,0.2081111,0.0008937987,0.3569687,0.01241947,0.3988869],"study_design_scores_gemma":[0.002102643,0.0008913616,0.0009486942,0.001359178,0.001013326,0.000236837,0.00008255611,0.4869437,0.001020999,0.4999085,0.00534665,0.0001456389],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001327778,0.0007799871,0.9954199,0.0004957307,0.0001089878,0.001274565,0.0000641786,0.0001848704,0.0003439629],"genre_scores_gemma":[0.04678622,0.000776261,0.9432451,0.0006357772,0.0002367469,0.007687544,0.0001563687,0.00009665392,0.0003793122],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7676139,"threshold_uncertainty_score":0.9466045,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2072546393","doi":"10.3102/1076998606298037","title":"Point Estimates and Confidence Intervals for Variable Importance in Multiple Linear Regression","year":2007,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":30,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Statistics Canada; Carleton University","funders":"","keywords":"Statistics; Confidence interval; Linear regression; Variable (mathematics); Regression analysis; Mathematics; Measure (data warehouse); Variance (accounting); Regression; Linear model; Regression diagnostic; Econometrics; Bayesian multivariate linear regression; Computer science; Data mining","authors":[{"name":"David R. Thomas","is_ca":true},{"name":"Pengcheng Zhu","is_ca":true},{"name":"Yves Decady","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1748694814327777,"gpt":0.4944659832462644,"spread":0.3195965018134866,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.07495872,0.001590294,0.002788023,0.007605434,0.0007629839,0.003755733,0.00519698,0.003518416,0.004078543],"category_scores_gemma":[0.5423942,0.0008657075,0.002264155,0.008394957,0.003408265,0.005265206,0.003548037,0.006080374,0.001113406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00136324,"about_ca_system_score_gemma":0.0009546171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001477968,"about_ca_topic_score_gemma":0.0006072588,"domain_scores_codex":[0.9037481,0.07285565,0.003434014,0.00540918,0.01379096,0.0007620077],"domain_scores_gemma":[0.3562389,0.6088876,0.0126756,0.01260328,0.009004243,0.0005903803],"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":[0.0007811586,0.000162148,0.01603771,0.003091754,0.001329879,0.0005310364,0.00113316,0.1121917,0.0009386392,0.4459245,0.009297959,0.4085804],"study_design_scores_gemma":[0.0001537447,0.0004538293,0.01397875,0.002433802,0.0006047304,0.001151929,0.0003909432,0.2659588,0.002476458,0.6989138,0.0132062,0.0002769418],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008676873,0.01328766,0.97414,0.0005393049,0.0002662684,0.0001007049,0.0003400439,0.000432421,0.002216737],"genre_scores_gemma":[0.4579352,0.01441266,0.5204049,0.000489629,0.001586763,0.001186252,0.001846602,0.0006977693,0.001440202],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07495872,"threshold_uncertainty_score":0.3964244,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2127843972","doi":"10.3102/1076998614524823","title":"A State Space Modeling Approach to Mediation Analysis","year":2014,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":29,"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":"Mediation; Computer science; Process (computing); Population; State space; Data science; Econometrics; Mathematics; Statistics; Sociology; Social science","authors":[{"name":"Фэй Гу","is_ca":true},{"name":"Kristopher J. Preacher","is_ca":false},{"name":"Emilio Ferrer","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1615246983656391,"gpt":0.4451226269014738,"spread":0.2835979285358347,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02199122,0.001888843,0.002514742,0.003536059,0.001935202,0.003596192,0.004506608,0.00272827,0.01727313],"category_scores_gemma":[0.04208041,0.0008357617,0.004134469,0.004820289,0.00250978,0.003965222,0.003962656,0.006059041,0.001405686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002779241,"about_ca_system_score_gemma":0.005693382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007519131,"about_ca_topic_score_gemma":0.005909486,"domain_scores_codex":[0.9741587,0.02094092,0.0006579779,0.001857742,0.001734713,0.0006499126],"domain_scores_gemma":[0.9719686,0.024042,0.001194344,0.001303622,0.001219163,0.0002723118],"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":[0.00006450705,0.00014558,0.002885143,0.0002528592,0.0006530395,0.0001766985,0.001024655,0.02308813,0.0002155633,0.9371322,0.002650924,0.03171063],"study_design_scores_gemma":[0.00008039114,0.0001926006,0.00111673,0.0001285011,0.0002853728,0.000134314,0.0003732631,0.1697336,0.0003121465,0.8154033,0.01217414,0.00006570708],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002826129,0.000444679,0.9898032,0.001550955,0.0001268754,0.0002756434,0.000348295,0.0001669398,0.004457254],"genre_scores_gemma":[0.3039911,0.002662712,0.6759526,0.001206594,0.0005613056,0.004714734,0.0008111545,0.0001699432,0.009929989],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02199122,"threshold_uncertainty_score":0.1163021,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2663249513","doi":"10.3102/1076998616680841","title":"A Strategy for Replacing Sum Scoring","year":2016,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":26,"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":"Univariate; Mathematics; Parametric statistics; Statistics; Odds; Function (biology); Statistical hypothesis testing; Test (biology); Binary number; Applied mathematics; Binary data; Algorithm; Computer science; Multivariate statistics; Logistic regression; Arithmetic","authors":[{"name":"J. O. Ramsay","is_ca":true},{"name":"Marie Wiberg","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2861209535314837,"gpt":0.5117877317198253,"spread":0.2256667781883416,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01368529,0.001771771,0.001802223,0.002371031,0.002058885,0.003544755,0.004011787,0.002423532,0.01611116],"category_scores_gemma":[0.06521629,0.0008339519,0.00156074,0.003568006,0.003761668,0.006021507,0.005647826,0.006306489,0.01327937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008813047,"about_ca_system_score_gemma":0.00259485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001443456,"about_ca_topic_score_gemma":0.001897625,"domain_scores_codex":[0.982139,0.007588404,0.001170685,0.002866742,0.005739508,0.0004956961],"domain_scores_gemma":[0.9760013,0.007075582,0.00114322,0.01093695,0.004311268,0.0005316912],"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":[0.0001732684,0.0001554032,0.002082339,0.000204888,0.00009405654,0.000213354,0.001139578,0.002157052,0.004331016,0.4847489,0.02983502,0.4748652],"study_design_scores_gemma":[0.00009780515,0.0004954731,0.001771321,0.0003841106,0.0001283857,0.002060655,0.0006682329,0.02956674,0.0116478,0.6267201,0.3262393,0.0002200532],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005215624,0.0003380952,0.9723606,0.003429034,0.001614084,0.0001780704,0.0002024243,0.001403574,0.0152586],"genre_scores_gemma":[0.05022678,0.0003637263,0.9291699,0.002252397,0.0005779189,0.000543892,0.0002029373,0.0009847139,0.01567776],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01611116,"threshold_uncertainty_score":0.0723756,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2984476219","doi":"10.3102/1076998619885636","title":"Full Information Optimal Scoring","year":2019,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Ottawa Hospital; McGill University","funders":"","keywords":"Statistics; Binary number; Scoring rule; Mathematics; Binary data; Scoring system; Computer science; Point (geometry); Test (biology); Mean squared error; Arithmetic; Medicine","authors":[{"name":"J. O. Ramsay","is_ca":true},{"name":"Marie Wiberg","is_ca":false},{"name":"Juan Li","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3522251289511596,"gpt":0.4970637307263445,"spread":0.1448386017751849,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01710184,0.001685117,0.002813077,0.003399915,0.000677508,0.003039986,0.00262526,0.001928827,0.007401206],"category_scores_gemma":[0.08574058,0.001257737,0.00171007,0.00326302,0.002125884,0.004608592,0.005312946,0.002528484,0.002642864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001186081,"about_ca_system_score_gemma":0.001994303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001229944,"about_ca_topic_score_gemma":0.001223344,"domain_scores_codex":[0.9652968,0.02029377,0.00246086,0.003439441,0.007267433,0.001241786],"domain_scores_gemma":[0.9579268,0.02064258,0.001773369,0.01251678,0.006582701,0.0005577871],"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":[0.001034642,0.0002946014,0.005110035,0.0003187716,0.0003588629,0.0001524944,0.0002451521,0.06025653,0.003222622,0.07308504,0.01233028,0.843591],"study_design_scores_gemma":[0.0003189293,0.0005077505,0.00534604,0.0001956811,0.0002075187,0.0006319068,0.00009557696,0.6658161,0.0079523,0.3088784,0.009813498,0.0002361608],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01673786,0.0007586259,0.9739218,0.000400008,0.0001311919,0.0002541391,0.0004497081,0.0008231261,0.006523633],"genre_scores_gemma":[0.2418703,0.0005096319,0.752017,0.0003876731,0.0001472163,0.000469653,0.00115337,0.0002862606,0.003158857],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01710184,"threshold_uncertainty_score":0.09044427,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2753556883","doi":"10.3102/1076998617694880","title":"Normal Theory Two-Stage ML Estimator When Data Are Missing at the Item Level","year":2017,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":9,"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":"Missing data; Imputation (statistics); Computer science; Estimator; Item response theory; Statistics; Structural equation modeling; Scale (ratio); Data mining; Mathematics; Psychometrics","authors":[{"name":"Victoria Savalei","is_ca":true},{"name":"Mijke Rhemtulla","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.7867101434106125,"gpt":0.5828149761437459,"spread":0.2038951672668666,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0184181,0.001477821,0.002457174,0.001916041,0.0008564277,0.002527051,0.004368915,0.001912388,0.01315482],"category_scores_gemma":[0.1193472,0.001106247,0.001740258,0.002705788,0.001897124,0.00445031,0.00317385,0.004076978,0.004065627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001208666,"about_ca_system_score_gemma":0.003240145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003332593,"about_ca_topic_score_gemma":0.003206863,"domain_scores_codex":[0.9810091,0.01319597,0.0007993506,0.002517763,0.002075933,0.0004018778],"domain_scores_gemma":[0.951017,0.03762055,0.00203359,0.005520322,0.00350185,0.0003066572],"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":[0.0005074057,0.00027096,0.02371455,0.001245891,0.001071003,0.0003971699,0.001200187,0.06920498,0.00220298,0.2860189,0.02316122,0.5910047],"study_design_scores_gemma":[0.000242051,0.0003528495,0.006318857,0.0003697352,0.0003339411,0.0006685191,0.0003676164,0.6173984,0.003068734,0.3422989,0.02845529,0.00012514],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001914061,0.0001876943,0.9958961,0.0002000637,0.00005970052,0.0001345929,0.0001669777,0.0003547847,0.001086081],"genre_scores_gemma":[0.1463079,0.0006257332,0.8433225,0.0006569746,0.0002899216,0.002015679,0.001392194,0.0004537538,0.004935432],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0184181,"threshold_uncertainty_score":0.09740543,"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":"W2883355895","doi":"10.3102/1076998618787478","title":"An Information Matrix Test for the Collapsing of Categories Under the Partial Credit Model","year":2018,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Goodness of fit; Econometrics; Test statistic; Set (abstract data type); Statistic; Test (biology); Polytomous Rasch model; Computer science; Statistics; Data set; Ordinal data; Mathematics; Data mining; Statistical hypothesis testing; Item response theory; Psychometrics","authors":[{"name":"Daphna Harel","is_ca":false},{"name":"Russell Steele","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.4011186254261651,"gpt":0.5242410804061896,"spread":0.1231224549800244,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05811315,0.001433458,0.002106517,0.006113465,0.001936864,0.002165774,0.003212971,0.002273396,0.01027789],"category_scores_gemma":[0.3720167,0.0005999394,0.003052881,0.005725828,0.004417795,0.005729861,0.00322924,0.003965284,0.001075761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001555047,"about_ca_system_score_gemma":0.002955841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00140808,"about_ca_topic_score_gemma":0.0009767867,"domain_scores_codex":[0.9122729,0.05852652,0.005013337,0.00737509,0.01577376,0.001038454],"domain_scores_gemma":[0.5716571,0.3854425,0.01262317,0.01762854,0.01119659,0.001452219],"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":[0.003397604,0.001041235,0.1917419,0.001690696,0.005430215,0.001448398,0.006066375,0.03718402,0.005414763,0.2392177,0.01835748,0.4890096],"study_design_scores_gemma":[0.0006875629,0.005085516,0.1105775,0.0007465635,0.001064798,0.001840293,0.002896531,0.4848767,0.008692978,0.3678569,0.01520281,0.0004718507],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1139614,0.0002418536,0.8730437,0.0009471445,0.0001561104,0.001623422,0.001489324,0.0007975931,0.007739515],"genre_scores_gemma":[0.6432201,0.0001479515,0.349124,0.0003754886,0.0001227907,0.004400617,0.001506743,0.0001658446,0.0009365577],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05811315,"threshold_uncertainty_score":0.3073354,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2157756920","doi":"10.3102/1076998615589129","title":"Visualizing Confidence Bands for Semiparametrically Estimated Nonlinear Relations Among Latent Variables","year":2015,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Mental Health Research Topics","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"American Educational Research Association","keywords":"Latent variable; Structural equation modeling; Inference; Computer science; Latent variable model; Statistical inference; Visualization; Exploratory data analysis; Econometrics; Regression analysis; Latent class model; Empirical research; Nonlinear system; Data mining; Artificial intelligence; Machine learning; Statistics; Mathematics","authors":[{"name":"Jolynn Pek","is_ca":true},{"name":"R. Philip Chalmers","is_ca":true},{"name":"Bethany E. Kok","is_ca":false},{"name":"Diane Losardo","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2731813646370473,"gpt":0.5297634161063589,"spread":0.2565820514693116,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02935016,0.00149673,0.0009907278,0.006468991,0.0006380712,0.004023313,0.001881564,0.002327635,0.01476543],"category_scores_gemma":[0.1989066,0.000833546,0.001245577,0.00273221,0.001317875,0.003881205,0.003538881,0.003086301,0.001084698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008420997,"about_ca_system_score_gemma":0.0007889753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002688324,"about_ca_topic_score_gemma":0.001495798,"domain_scores_codex":[0.9934227,0.004398646,0.0004549632,0.0006134483,0.0009082674,0.0002019463],"domain_scores_gemma":[0.7544731,0.2238864,0.006614272,0.00941151,0.004957441,0.0006572991],"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":[0.001673808,0.0003431661,0.03081997,0.002134844,0.0004702804,0.0008838468,0.0110398,0.1635059,0.008269751,0.24457,0.02795596,0.5083327],"study_design_scores_gemma":[0.0002204115,0.0002501826,0.01793371,0.001057298,0.0001591531,0.0007301744,0.002012985,0.7340534,0.00976091,0.21692,0.01665455,0.0002473316],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0454221,0.0005993607,0.9411324,0.0008609215,0.00008140317,0.00009745322,0.001177989,0.007209174,0.003419185],"genre_scores_gemma":[0.476968,0.0003972104,0.51801,0.0001896607,0.00008685877,0.0005663685,0.001419359,0.001653527,0.0007090417],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02935016,"threshold_uncertainty_score":0.1552203,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2060741340","doi":"10.3102/10769986028001083","title":"A Review of <i>Data Analysis for the Behavioral Sciences Using SPSS</i>","year":2003,"lang":"en","type":"review","venue":"Journal of Educational and Behavioral Statistics","topic":"Statistics Education and Methodologies","field":"Mathematics","cited_by":3,"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":"Statistics education; Mathematics education; Readability; Computer science; Competence (human resources); Statistics; Psychology; Mathematics; Social psychology","authors":[{"name":"Kim Koh","is_ca":true},{"name":"Murlita P. Witarsa","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.8292002256135855,"gpt":0.6501527572032614,"spread":0.1790474684103242,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008417669,0.001156303,0.00211762,0.0115572,0.0006048108,0.002093561,0.001844958,0.001485567,0.007022548],"category_scores_gemma":[0.02575854,0.0008504356,0.002174181,0.01491422,0.001574629,0.003431706,0.001119376,0.002769413,0.005406169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002544497,"about_ca_system_score_gemma":0.006946282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005057519,"about_ca_topic_score_gemma":0.00720306,"domain_scores_codex":[0.9907814,0.002808318,0.002155339,0.0006275773,0.00344197,0.0001853192],"domain_scores_gemma":[0.9628758,0.02591179,0.002354263,0.0005204412,0.007931942,0.0004057728],"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":[0.00004358045,0.00006170353,0.0006012729,0.05658716,0.0001836563,0.0001447577,0.0004870633,0.000353054,0.0007674973,0.005073395,0.2199301,0.7157668],"study_design_scores_gemma":[0.000009462178,0.0001032953,0.004357127,0.03527737,0.0001513003,0.0004306248,0.0002559467,0.0001957479,0.0003598229,0.002523433,0.9562827,0.00005323874],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002268748,0.9819714,0.006437905,0.004947853,0.002347541,0.0001357142,0.0004658382,0.0001957319,0.003271112],"genre_scores_gemma":[0.001337761,0.9837337,0.007405967,0.003725954,0.001452331,0.0003329134,0.0005129966,0.00009199991,0.001406374],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.0115572,"threshold_uncertainty_score":0.0445174,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W346574303","doi":"10.3102/10769986030004353","title":"No Humble Pie: The Origins and Usage of a Statistical Chart","year":2005,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Data Visualization and Analytics","field":"Computer Science","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 Toronto","funders":"","keywords":"Chart; Pie chart; Appeal; Brother; Plot (graphics); History; Mathematics; Law; Statistics; Political science","authors":[{"name":"Ian Spence","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04239665616900781,"gpt":0.3786457753845167,"spread":0.3362491192155089,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02286728,0.0008164385,0.0008447196,0.004755121,0.004470534,0.01357301,0.001873768,0.003241984,0.005319961],"category_scores_gemma":[0.1627503,0.0006267175,0.0005617901,0.006441672,0.02460124,0.01359185,0.003396478,0.007020762,0.00143259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003135103,"about_ca_system_score_gemma":0.004699576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006564342,"about_ca_topic_score_gemma":0.006607598,"domain_scores_codex":[0.9762217,0.01678538,0.001122106,0.001417585,0.00398768,0.0004655734],"domain_scores_gemma":[0.9071105,0.07603705,0.002472481,0.005217673,0.008090166,0.001072054],"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":[0.00003884559,0.000004319075,0.0003423346,0.00005718193,0.000005506987,0.00006054685,0.003583995,0.0002760304,0.00006235288,0.9356617,0.0256722,0.03423494],"study_design_scores_gemma":[0.00001172628,0.00002358254,0.0005612014,0.0005071744,0.00001057242,0.000223664,0.001831015,0.001876299,0.0004160353,0.64867,0.3457945,0.00007437781],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01460605,0.02805935,0.6217366,0.1613906,0.01491161,0.0001529796,0.0009375518,0.002172032,0.1560332],"genre_scores_gemma":[0.4912896,0.02564791,0.3805388,0.03310618,0.01347924,0.0006860345,0.0007794122,0.004896711,0.04957599],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02286728,"threshold_uncertainty_score":0.1209351,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2095820822","doi":"10.3102/1076998610397052","title":"Sampling Variability and Axioms of Classical Test Theory","year":2011,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Mathematics; Statistics; Sampling (signal processing); Sample size determination; Statistical hypothesis testing; Test theory; Sample (material); Test (biology); Axiom; Reliability (semiconductor); Population; Applied mathematics; Psychometrics; Computer science; Geometry","authors":[{"name":"Donald W. Zimmerman","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.6043028112079372,"gpt":0.5189607433140067,"spread":0.0853420678939305,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05315699,0.001001787,0.002575294,0.003622723,0.001789615,0.004700808,0.004469867,0.002484474,0.003777306],"category_scores_gemma":[0.2204103,0.0009779917,0.002196445,0.002954523,0.01354864,0.006757646,0.005487541,0.006206825,0.001098517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002844684,"about_ca_system_score_gemma":0.002794921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003161281,"about_ca_topic_score_gemma":0.001403925,"domain_scores_codex":[0.9454123,0.02581417,0.003626024,0.008717971,0.01527478,0.001154712],"domain_scores_gemma":[0.7803366,0.177596,0.006936162,0.02102841,0.01326101,0.0008417424],"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":[0.00004228337,0.00003965172,0.003227971,0.0001799852,0.0001002532,0.0001257433,0.0006232903,0.01305515,0.0002898854,0.9496275,0.001559565,0.03112869],"study_design_scores_gemma":[0.00003492427,0.00004273868,0.00165175,0.0001081217,0.00002574418,0.0002002632,0.000068418,0.03201616,0.0003694598,0.9615014,0.003943918,0.00003709803],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008071425,0.0006852314,0.9799565,0.001215434,0.0001868702,0.0001484118,0.0002264343,0.000182438,0.009327265],"genre_scores_gemma":[0.4291905,0.001995763,0.5564993,0.002003162,0.001377793,0.002803,0.0009638516,0.0003358985,0.004830698],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05315699,"threshold_uncertainty_score":0.2811244,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2461458402","doi":"10.3102/1076998615625963","title":"A Review of <i>Monte Carlo Simulation and Resampling Methods for Social Science</i>","year":2016,"lang":"en","type":"review","venue":"Journal of Educational and Behavioral Statistics","topic":"Opinion Dynamics and Social Influence","field":"Physics and Astronomy","cited_by":1,"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":"Monte Carlo method; Resampling; Computer science; Statistics; Mathematics; Artificial intelligence","authors":[{"name":"Фэй Гу","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1585917114809376,"gpt":0.5628150157069903,"spread":0.4042233042260527,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01335723,0.001636006,0.003455768,0.005047064,0.0005738135,0.00268614,0.003519153,0.002857317,0.005478688],"category_scores_gemma":[0.04314721,0.000776138,0.001748334,0.009561797,0.001931791,0.003306611,0.001481514,0.00290538,0.00253915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002012975,"about_ca_system_score_gemma":0.004459397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008697914,"about_ca_topic_score_gemma":0.009047463,"domain_scores_codex":[0.9944042,0.002978282,0.0006509211,0.0006582084,0.001199497,0.0001088721],"domain_scores_gemma":[0.9620807,0.03275604,0.0009433,0.001113439,0.002858556,0.0002479794],"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":[0.00006191229,0.00009493366,0.0009842925,0.01196352,0.0004098683,0.00005711754,0.000150796,0.006148567,0.0002691698,0.06468908,0.05056038,0.8646103],"study_design_scores_gemma":[0.00009130361,0.0002234891,0.003449677,0.01226789,0.0007464599,0.0005938472,0.0001490383,0.02864289,0.00110407,0.1928491,0.7596238,0.000258317],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004271455,0.9017743,0.08870535,0.004190369,0.001380106,0.00006955471,0.0003627951,0.0002378522,0.00285251],"genre_scores_gemma":[0.009102348,0.882413,0.09941091,0.002354211,0.004084605,0.0002950656,0.0005706752,0.000213443,0.001555718],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01335723,"threshold_uncertainty_score":0.07064056,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4388459609","doi":"10.3102/10769986231207879","title":"Analyzing Polytomous Test Data: A Comparison Between an Information-Based IRT Model and the Generalized Partial Credit Model","year":2023,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Ottawa Hospital; McGill University","funders":"","keywords":"Polytomous Rasch model; Item response theory; Measure (data warehouse); Econometrics; Computer science; Statistics; Metric (unit); Parametric statistics; Nonparametric statistics; Scale (ratio); Psychometrics; Mathematics; Data mining","authors":[{"name":"Joakim Wallmark","is_ca":false},{"name":"J. O. Ramsay","is_ca":true},{"name":"Juan Li","is_ca":true},{"name":"Marie Wiberg","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.5966527320784061,"gpt":0.5378534698798701,"spread":0.05879926219853593,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04464492,0.001527421,0.002679079,0.003378359,0.0006146588,0.003354215,0.004956266,0.002458462,0.003059913],"category_scores_gemma":[0.1641319,0.0006520514,0.002564164,0.004934519,0.00372733,0.006465808,0.002378016,0.003794333,0.0008178997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002461497,"about_ca_system_score_gemma":0.002503288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006543194,"about_ca_topic_score_gemma":0.004689767,"domain_scores_codex":[0.9712602,0.02262744,0.0007140627,0.002529772,0.002405392,0.0004632052],"domain_scores_gemma":[0.8024222,0.1676361,0.006324875,0.01762825,0.005020687,0.00096798],"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":[0.001104946,0.0004179459,0.04295959,0.0006212487,0.001170092,0.0003772958,0.001325476,0.5848984,0.0005742207,0.1757576,0.003993157,0.1868001],"study_design_scores_gemma":[0.00008228224,0.0002022703,0.005854757,0.00006985068,0.00009238995,0.0001379124,0.0001582688,0.89072,0.0001963985,0.1013832,0.001042093,0.00006061289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1137133,0.00100348,0.8789225,0.001885594,0.00008104289,0.0003550726,0.0006312557,0.0006039861,0.002803725],"genre_scores_gemma":[0.7795544,0.0007486405,0.2134372,0.0007995256,0.0002000083,0.0009446088,0.001914838,0.0003331674,0.002067592],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04464492,"threshold_uncertainty_score":0.2361077,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2290377455","doi":"10.3102/1076998615606114","title":"Graphs ′ <i>R</i> Us UnwinAntony. Graphical Data Analysis With R. Boca Raton, FL: Taylor &amp; Francis, 2015; 310 pages, $69.95, ISBN 9781498715232.","year":2015,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Advanced Graph Theory Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Computer science; Mathematics education; Mathematics","authors":[{"name":"Howard Wainer","is_ca":false},{"name":"Michael Friendly","is_ca":true},{"name":"Pere Millán‐Martínez","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08435273792904979,"gpt":0.3799160870258571,"spread":0.2955633490968073,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004546951,0.002076594,0.001617466,0.00412476,0.0009857847,0.003220491,0.002617262,0.001374268,0.1939135],"category_scores_gemma":[0.04901372,0.001881992,0.001865358,0.007719184,0.002522293,0.004868443,0.002389526,0.003354582,0.10321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009720983,"about_ca_system_score_gemma":0.002100284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003512189,"about_ca_topic_score_gemma":0.006092787,"domain_scores_codex":[0.9951266,0.001903741,0.0004260753,0.001370261,0.0009852861,0.0001879865],"domain_scores_gemma":[0.972514,0.01834982,0.001933992,0.004783027,0.002052185,0.0003669098],"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":[0.00006236671,0.00002554584,0.0005030205,0.001698753,0.0001285346,0.0001605347,0.0002944188,0.001267054,0.001125531,0.05679865,0.776827,0.1611086],"study_design_scores_gemma":[0.00002647677,0.00002897815,0.0008741133,0.0005413236,0.0000974487,0.0006459063,0.000117303,0.003795275,0.001711619,0.1564176,0.8356753,0.00006873801],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.001838064,0.02131279,0.8132481,0.01179442,0.006452147,0.0002157083,0.05632377,0.02984296,0.05897214],"genre_scores_gemma":[0.06642734,0.0293896,0.7104236,0.0090976,0.004897903,0.002210098,0.06070954,0.04116236,0.07568201],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1939135,"threshold_uncertainty_score":0.6487051,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4407927480","doi":"10.3102/10769986251314833","title":"Using the Information Metric to Analyze Clinical Rating Scales","year":2025,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Dalhousie University; University of Manitoba; Ottawa Hospital; McGill University","funders":"Vetenskapsrådet","keywords":"Rating scale; Metric (unit); Item response theory; Statistics; Computer science; Econometrics; Mathematics; Psychology; Psychometrics","authors":[{"name":"J. O. Ramsay","is_ca":true},{"name":"Juan Li","is_ca":true},{"name":"Charles N. Bernstein","is_ca":true},{"name":"Ruth Ann Marrie","is_ca":true},{"name":"Joakim Wallmark","is_ca":false},{"name":"Marie Wiberg","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.4986897028064809,"gpt":0.5681965655826773,"spread":0.06950686277619639,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03644506,0.001205799,0.001355167,0.009503247,0.0007497919,0.004079932,0.001435326,0.001290756,0.003222051],"category_scores_gemma":[0.228539,0.0004370169,0.001498742,0.007772556,0.002918162,0.004431316,0.002610361,0.002614717,0.0007712235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001918244,"about_ca_system_score_gemma":0.001601814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001259348,"about_ca_topic_score_gemma":0.0007355437,"domain_scores_codex":[0.954801,0.02688146,0.003901229,0.002704364,0.01126867,0.0004433709],"domain_scores_gemma":[0.8152895,0.1482848,0.01178144,0.01085133,0.0129121,0.0008807812],"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":[0.0003739272,0.0002090654,0.0397396,0.001039492,0.0007702569,0.0006160815,0.002791192,0.08574845,0.003898033,0.3766796,0.01109594,0.4770383],"study_design_scores_gemma":[0.00006601738,0.0006320915,0.02164849,0.0003352006,0.000146365,0.0008917175,0.000920725,0.4207359,0.002916399,0.5337713,0.01771426,0.0002215574],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01113714,0.0004391147,0.9840528,0.0004582298,0.00009330142,0.0002699465,0.0004319968,0.0002872006,0.002830205],"genre_scores_gemma":[0.3345772,0.0005482316,0.6603304,0.0003642702,0.0002822939,0.001458429,0.001131764,0.0002609169,0.001046412],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03644506,"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":"grok","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":"W4415958133","doi":"10.3102/10769986251379738","title":"Valid Standard Errors for Bayesian Quantile Regression With Clustered and Independent Data","year":2025,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada; Canada Research Chairs","keywords":"Jackknife resampling; Frequentist inference; Markov chain Monte Carlo; Estimator; Quantile; Quantile regression; Standard error; Bayesian probability; Point estimation; Outlier","authors":[{"name":"Feng Ji","is_ca":true},{"name":"Joon-Ho Lee","is_ca":false},{"name":"Sophia Rabe‐Hesketh","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06763164808331662,"gpt":0.405548800795139,"spread":0.3379171527118224,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05317607,0.001301351,0.002002734,0.003876407,0.001170383,0.002895397,0.005816476,0.002926395,0.0109723],"category_scores_gemma":[0.3909529,0.001202431,0.002859199,0.005554142,0.002152552,0.003877033,0.002883926,0.005889873,0.003888691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001946385,"about_ca_system_score_gemma":0.002377779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004622117,"about_ca_topic_score_gemma":0.004356858,"domain_scores_codex":[0.9565806,0.02421933,0.003539046,0.0057945,0.009026025,0.0008405149],"domain_scores_gemma":[0.8116549,0.1277073,0.01074999,0.03717196,0.01206728,0.0006485289],"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":[0.0001941081,0.0002137758,0.01591968,0.0009673954,0.00125145,0.0003243524,0.00114482,0.07539611,0.001331414,0.5624899,0.04156706,0.2991999],"study_design_scores_gemma":[0.0001294168,0.000137071,0.009859416,0.000921212,0.0003191871,0.0003634678,0.0003007052,0.1731939,0.004743035,0.761743,0.04811629,0.0001732676],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00281178,0.0004435461,0.9931297,0.0002962017,0.0002516232,0.0001320526,0.000649008,0.0008448527,0.00144119],"genre_scores_gemma":[0.1416367,0.0007392753,0.8464134,0.0006730799,0.0003783022,0.002287308,0.0025151,0.002242808,0.003114006],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05317607,"threshold_uncertainty_score":0.2812253,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}