{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":33,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":33,"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":"ba0f37fc5bf0","filters":{"venue":"Sociological Methods & Research"}},"results":[{"id":"W2321084336","doi":"10.1177/0049124114547769","title":"What You Can—and Can’t—Do With Three-Wave Panel Data","year":2014,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Social Capital and Networks","field":"Social Sciences","cited_by":310,"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; Context (archaeology); Panel data; Sign (mathematics); Computer science; Simple (philosophy); Constant (computer programming); Specification; Point (geometry); Statistics; Mathematics; Epistemology","authors":[{"name":"Stephen Vaisey","is_ca":false},{"name":"Andrew Miles","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.6132883582648904,"gpt":0.5563295464419532,"spread":0.05695881182293716,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.060897,0.001217049,0.00221733,0.001983131,0.003292027,0.00628484,0.004241726,0.00639815,0.01065165],"category_scores_gemma":[0.2614003,0.001116636,0.002045112,0.005466869,0.007020522,0.02117618,0.003528106,0.009159235,0.00327672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001707395,"about_ca_system_score_gemma":0.001892995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01122032,"about_ca_topic_score_gemma":0.009726258,"domain_scores_codex":[0.9426373,0.04921738,0.001106059,0.003211024,0.002990085,0.0008380899],"domain_scores_gemma":[0.831542,0.1250726,0.00999211,0.02675523,0.004785831,0.001852143],"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":[0.0002355809,0.000291305,0.03648858,0.002005832,0.001871809,0.0004371785,0.004931785,0.01017511,0.0003772054,0.5076525,0.1746906,0.2608425],"study_design_scores_gemma":[0.00008671545,0.0001058547,0.004936767,0.001765587,0.0002407141,0.0002112722,0.001435985,0.01035606,0.0004497617,0.9055805,0.07467035,0.0001604265],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02358213,0.0218226,0.5112886,0.4031453,0.006732177,0.0004901945,0.005374087,0.0007519803,0.02681297],"genre_scores_gemma":[0.3802779,0.03008655,0.4601183,0.098704,0.010999,0.002478927,0.003716858,0.0005965517,0.01302196],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.939103,"threshold_uncertainty_score":0.322058,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1963762678","doi":"10.1177/0049124106292362","title":"Addressing Data Sparseness in Contextual Population Research","year":2007,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":172,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Variance (accounting); Cluster analysis; Cluster (spacecraft); Monte Carlo method; Statistics; Population; Econometrics; Data mining; Machine learning; Mathematics","authors":[{"name":"Philippa Clarke","is_ca":false},{"name":"Blair Wheaton","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.9296372523519871,"gpt":0.7377377898052143,"spread":0.1918994625467728,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1811995,0.0006394638,0.002463077,0.003582651,0.003217596,0.004060063,0.002958448,0.003889059,0.001767761],"category_scores_gemma":[0.5553102,0.001159065,0.001160708,0.006575675,0.007251444,0.006346717,0.005316296,0.004255379,0.0002026275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002478938,"about_ca_system_score_gemma":0.004684114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005005651,"about_ca_topic_score_gemma":0.005165317,"domain_scores_codex":[0.7259731,0.2490119,0.005693189,0.006976666,0.0115578,0.0007872321],"domain_scores_gemma":[0.3056238,0.6421299,0.01706518,0.02446749,0.009769466,0.0009440961],"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":[0.000532302,0.0003859667,0.137188,0.00427311,0.002429044,0.001073697,0.01689847,0.0937411,0.001083178,0.512116,0.00678453,0.2234947],"study_design_scores_gemma":[0.0001495159,0.0006216357,0.02242873,0.0024502,0.0005164599,0.0007927401,0.00409503,0.1549721,0.001744057,0.7933903,0.01866411,0.0001751283],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06528195,0.003475727,0.9174967,0.008413354,0.0002977509,0.00070326,0.0002592761,0.0001676258,0.003904391],"genre_scores_gemma":[0.682825,0.001872779,0.3099285,0.00280129,0.0003040543,0.001615971,0.0002021155,0.00008158763,0.0003687444],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1811995,"threshold_uncertainty_score":0.9582859,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2887293044","doi":"10.1177/0049124118789717","title":"A Note on a Reformulation of the KHB Method","year":2018,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":106,"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":"Logit; Probit; Statistics; Mathematics; Probit model; Logistic regression; Econometrics; Residual; Confounding; Variance (accounting); Constant (computer programming); Conditional probability; Conditional logistic regression; Computer science; Economics; Algorithm","authors":[{"name":"Richard Breen","is_ca":false},{"name":"Kristian Bernt Karlson","is_ca":false},{"name":"Anders Holm","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.4082641240265609,"gpt":0.5321633408856649,"spread":0.123899216859104,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04024381,0.001090733,0.002266111,0.003086681,0.001929284,0.005946775,0.004879026,0.00310216,0.0213119],"category_scores_gemma":[0.1441965,0.001438844,0.00233214,0.004355635,0.004119116,0.006457332,0.006010916,0.01113663,0.01536008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002038985,"about_ca_system_score_gemma":0.004848289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008003267,"about_ca_topic_score_gemma":0.006975451,"domain_scores_codex":[0.9591445,0.02865112,0.002017676,0.003310983,0.006233431,0.0006423796],"domain_scores_gemma":[0.9312354,0.04100076,0.002146677,0.0142219,0.01070427,0.0006910833],"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":[0.00009965121,0.00007719228,0.001476522,0.0003332842,0.0001202166,0.0002239231,0.001002479,0.002723419,0.001282591,0.6984279,0.08158474,0.2126482],"study_design_scores_gemma":[0.0001104374,0.00008377869,0.002250257,0.0005616765,0.00008827487,0.0006458109,0.0004289522,0.02889442,0.001322706,0.5924732,0.3728914,0.0002490528],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009463329,0.001097174,0.9829094,0.006223388,0.002544208,0.0001731228,0.0005403805,0.000550892,0.005015049],"genre_scores_gemma":[0.01652082,0.001422389,0.9653225,0.004222062,0.002041257,0.0007927741,0.0006602817,0.001366975,0.007650988],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04024381,"threshold_uncertainty_score":0.2128322,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4210644525","doi":"10.1177/00491241211036165","title":"Moving Beyond Linear Regression: Implementing and Interpreting Quantile Regression Models With Fixed Effects","year":2022,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":104,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Quantile regression; Econometrics; Regression; Quantile; Linear regression; Fixed effects model; Regression analysis; Replication (statistics); Range (aeronautics); Wage; Statistics; Computer science; Mathematics; Economics; Panel data","authors":[{"name":"Fernando Ríos‐Avila","is_ca":false},{"name":"Michelle Maroto","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3809058897593379,"gpt":0.5984629512409576,"spread":0.2175570614816197,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.07441774,0.001446966,0.002146353,0.002668306,0.001030847,0.005901637,0.004273809,0.002746186,0.005295557],"category_scores_gemma":[0.2380188,0.001014703,0.0033284,0.005182726,0.003836042,0.006662651,0.004189502,0.006709263,0.001204819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001977217,"about_ca_system_score_gemma":0.003327825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01593642,"about_ca_topic_score_gemma":0.008407128,"domain_scores_codex":[0.9301586,0.06132388,0.001592121,0.003099928,0.003052414,0.0007731825],"domain_scores_gemma":[0.8261511,0.1491432,0.008184696,0.01140839,0.004680841,0.0004316956],"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":[0.00009456136,0.00008205471,0.015604,0.001000335,0.0007319199,0.0004280078,0.004228794,0.03660353,0.0004478845,0.7807437,0.008254695,0.1517805],"study_design_scores_gemma":[0.00005446736,0.0001108841,0.004379037,0.001045807,0.000218722,0.0001301103,0.001135458,0.08725816,0.0009698127,0.8690458,0.03554846,0.0001032778],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005021138,0.00236435,0.9830927,0.004645051,0.0003347207,0.0001278011,0.0004110922,0.0004498398,0.003553303],"genre_scores_gemma":[0.1957043,0.004366926,0.7897656,0.003935885,0.0006859746,0.0008488811,0.0006591438,0.0007914064,0.00324197],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07441774,"threshold_uncertainty_score":0.3935633,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2224720476","doi":"10.1177/0049124115610345","title":"Obtaining Predictions from Models Fit to Multiply Imputed Data","year":2015,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":79,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Imputation (statistics); Set (abstract data type); Data set; Data mining; Missing data; Machine learning; Artificial intelligence","authors":[{"name":"Andrew Miles","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.8988619494689873,"gpt":0.6764142898064175,"spread":0.2224476596625699,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03193921,0.002053053,0.001999281,0.003053555,0.0009397486,0.003755794,0.003047804,0.00177421,0.007314072],"category_scores_gemma":[0.1764611,0.00177561,0.004048218,0.002877913,0.001693565,0.004205106,0.003119789,0.005975431,0.003614196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001916931,"about_ca_system_score_gemma":0.002378729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00673378,"about_ca_topic_score_gemma":0.006130042,"domain_scores_codex":[0.9782995,0.01529642,0.0009910653,0.002262042,0.002644797,0.0005062238],"domain_scores_gemma":[0.8692594,0.1100658,0.003871038,0.01173598,0.004626535,0.0004413391],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000404,0.0002579637,0.02769486,0.001293576,0.001655817,0.001248776,0.002179503,0.5252295,0.002462534,0.1759403,0.02103028,0.2406029],"study_design_scores_gemma":[0.00004815562,0.0001258795,0.003983446,0.0003668591,0.0001879313,0.0002849742,0.0003653349,0.7202096,0.003282237,0.2635331,0.007484125,0.000128278],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0142172,0.0001850259,0.9805986,0.0005347652,0.00006842508,0.0001551777,0.0006534717,0.001054041,0.002533328],"genre_scores_gemma":[0.2465434,0.0005693018,0.7446023,0.0004855439,0.0001052807,0.001028113,0.0027356,0.001312529,0.002617947],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9680608,"threshold_uncertainty_score":0.1689127,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2604981585","doi":"10.1177/0049124117701484","title":"The Relationship Between the Position of Name Generator Questions and Responsiveness in Multiple Name Generator Surveys","year":2017,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Survey Methodology and Nonresponse","field":"Social Sciences","cited_by":67,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Impact; McMaster University; Public Health Ontario; University of Toronto","funders":"","keywords":"Satisficing; Psychology; Social psychology; Generator (circuit theory); Position (finance); Computer science; Artificial intelligence; Business; Power (physics)","authors":[{"name":"Reza Yousefi‐Nooraie","is_ca":true},{"name":"Alexandra Marin","is_ca":true},{"name":"Robert Hanneman","is_ca":false},{"name":"Eleanor Pullenayegum","is_ca":true},{"name":"Lynne Lohfeld","is_ca":false},{"name":"Maureen Dobbins","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.7044616437765651,"gpt":0.6221866481149423,"spread":0.08227499566162277,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2301645,0.0006318131,0.000807424,0.002401778,0.00132916,0.002513726,0.00173154,0.00245125,0.005729997],"category_scores_gemma":[0.5699173,0.000850404,0.001471812,0.001969971,0.003003662,0.005223004,0.00363909,0.003434281,0.001193124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001258917,"about_ca_system_score_gemma":0.001343478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009293517,"about_ca_topic_score_gemma":0.0006964509,"domain_scores_codex":[0.610733,0.3471643,0.01339645,0.01057352,0.01458005,0.003552748],"domain_scores_gemma":[0.163667,0.7655799,0.03889298,0.0219047,0.007519989,0.002435355],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003759204,0.001499103,0.9108827,0.0006807023,0.0007227328,0.0004568418,0.02782595,0.004064704,0.004278713,0.003102025,0.0006341815,0.0420932],"study_design_scores_gemma":[0.0003988,0.01107336,0.9030678,0.0006091961,0.0007451104,0.00202176,0.01598549,0.03600385,0.01436922,0.01135647,0.003976024,0.0003930551],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9829107,0.000160484,0.01284771,0.0005385856,0.00003944556,0.0002895311,0.0001088422,0.00005491415,0.003049778],"genre_scores_gemma":[0.9963928,0.00003107971,0.002840041,0.0001410917,0.00002882029,0.0002283359,0.00007655317,0.00002208367,0.0002390958],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7698355,"threshold_uncertainty_score":0.9493443,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2159263306","doi":"10.1177/0049124107301944","title":"Log-Linear Randomized-Response Models Taking Self-Protective Response Behavior Into Account","year":2007,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":49,"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":"Randomized response; Respondent; Log-linear model; Response bias; Item response theory; Statistics; Outcome (game theory); Psychology; Social psychology; Econometrics; Response time; Linear model; Mathematics; Computer science; Psychometrics","authors":[{"name":"Maarten Cruyff","is_ca":false},{"name":"Ardo van den Hout","is_ca":false},{"name":"P.G.M. van der Heijden","is_ca":false},{"name":"Ulf Böckenholt","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.5305748280486128,"gpt":0.619559010240721,"spread":0.08898418219210824,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.08678734,0.00447549,0.005698329,0.004251203,0.001356942,0.004538485,0.01116488,0.007194211,0.03031829],"category_scores_gemma":[0.1860311,0.002775996,0.006703104,0.004603352,0.004632785,0.006105077,0.004107045,0.008153626,0.01057189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003892374,"about_ca_system_score_gemma":0.00240028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008139554,"about_ca_topic_score_gemma":0.004072947,"domain_scores_codex":[0.8925887,0.08978558,0.00271878,0.008790125,0.003461092,0.002655785],"domain_scores_gemma":[0.7565935,0.2109032,0.01246655,0.01233961,0.006915378,0.0007818782],"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":[0.004956143,0.001418494,0.04021686,0.003762038,0.004748489,0.00127914,0.005330686,0.3136908,0.0009903362,0.4523093,0.02209223,0.1492055],"study_design_scores_gemma":[0.001050568,0.001090997,0.003469306,0.0004108528,0.0008643856,0.0004839916,0.0005866892,0.7812199,0.0005488744,0.1986518,0.01140926,0.0002134161],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04215929,0.0014472,0.9383875,0.002977461,0.0006038152,0.004088894,0.004215129,0.002398804,0.003721809],"genre_scores_gemma":[0.4483863,0.00226068,0.4735275,0.002557288,0.0007506367,0.02461026,0.005517338,0.0005429739,0.04184696],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.08678734,"threshold_uncertainty_score":0.4589808,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2013108856","doi":"10.1177/0049124105280198","title":"Mapping Social Distance","year":2005,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":41,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Multidimensional scaling; Ethnic group; Census; Metropolitan area; Immigration; Diversity (politics); Geography; Social distance; Sociology; Social group; Racial diversity; Census tract; Cultural diversity; Geographical distance; Economic geography; Regional science; Demography; Demographic economics; Social science; Statistics; Mathematics; Anthropology; Population","authors":[{"name":"Michael J. White","is_ca":false},{"name":"Ann H. Kim","is_ca":false},{"name":"Jennifer E. Glick","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.496170104316695,"gpt":0.6084512661669489,"spread":0.1122811618502539,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005583155,0.0003970628,0.0002996772,0.007297107,0.001061586,0.002003712,0.0005048332,0.0004684281,0.007176226],"category_scores_gemma":[0.00609723,0.000137584,0.0004381109,0.006187335,0.0004872404,0.001379953,0.002301313,0.0003785917,0.00172455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006141687,"about_ca_system_score_gemma":0.0005755317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008951135,"about_ca_topic_score_gemma":0.009242971,"domain_scores_codex":[0.9988495,0.0003438917,0.00006434631,0.0002827484,0.0003555387,0.0001040422],"domain_scores_gemma":[0.998381,0.0007071233,0.0002249989,0.0002301185,0.0003562575,0.000100555],"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":[0.0001995543,0.0001903474,0.2537895,0.0006454251,0.0002252469,0.0004521729,0.01397368,0.01232159,0.006245315,0.05452901,0.01076645,0.6466617],"study_design_scores_gemma":[0.00004888682,0.000420279,0.536755,0.0004110018,0.0001558089,0.001725487,0.05260046,0.09654545,0.009727921,0.1262121,0.1751808,0.0002168629],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7456446,0.001262352,0.1692599,0.0005626908,0.0001350252,0.0003427188,0.009966224,0.0008560746,0.0719705],"genre_scores_gemma":[0.9355955,0.0003915147,0.05643403,0.00002758813,0.00001914454,0.0001806971,0.003002002,0.00008006662,0.004269463],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008951135,"threshold_uncertainty_score":0.02400684,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2802314382","doi":"10.1177/0049124118769087","title":"Regression-based Adjustment for Time-varying Confounders","year":2018,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":35,"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":"Marginal structural model; Econometrics; Estimator; Inverse probability; Regression; Average treatment effect; Statistics; Propensity score matching; Matching (statistics); Regression analysis; Computer science; Conditional expectation; Observational study; Outcome (game theory); Confounding; Estimation; Mathematics; Economics; Bayesian probability","authors":[{"name":"Geoffrey T. Wodtke","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.6894510924192692,"gpt":0.6691776798557132,"spread":0.02027341256355597,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03124516,0.001403158,0.001966524,0.001560461,0.0005628746,0.001021941,0.00341263,0.001170481,0.004546224],"category_scores_gemma":[0.1010838,0.0007112029,0.0029176,0.003024286,0.0007594162,0.001795423,0.001876232,0.003167782,0.001217934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008369313,"about_ca_system_score_gemma":0.003159546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00811251,"about_ca_topic_score_gemma":0.005644895,"domain_scores_codex":[0.9826158,0.01320184,0.000610307,0.001987577,0.001190401,0.0003940745],"domain_scores_gemma":[0.9697847,0.01824352,0.003025795,0.006908947,0.001826617,0.0002103657],"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":[0.0006364142,0.0003821776,0.04145915,0.0009176156,0.003998749,0.0003258108,0.0009839383,0.1826231,0.004618431,0.2216329,0.00966442,0.5327574],"study_design_scores_gemma":[0.0003483602,0.0005874409,0.0213925,0.0002267585,0.001518049,0.0003343908,0.0002222348,0.7344689,0.006405735,0.2059084,0.02844294,0.0001442481],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007112032,0.000466221,0.9904594,0.0003722389,0.00009370167,0.0001231417,0.0001981329,0.0005166599,0.0006584257],"genre_scores_gemma":[0.2525566,0.0009562444,0.7396932,0.0003760249,0.000192684,0.0008267977,0.00101029,0.0004535112,0.003934804],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03124516,"threshold_uncertainty_score":0.1652421,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2983060199","doi":"10.1177/0049124119882460","title":"The Double Bind of Qualitative Comparative Analysis","year":2019,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Qualitative Comparative Analysis Research","field":"Social Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal","funders":"","keywords":"Qualitative comparative analysis; Computer science; Theoretical computer science; Simple (philosophy); Set (abstract data type); Algorithm; Face (sociological concept); Data mining; Machine learning; Epistemology","authors":[{"name":"Vincent Arel‐Bundock","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.817819447521365,"gpt":0.7678292769503934,"spread":0.04999017057097166,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.1992799,0.001296572,0.00305923,0.007324515,0.008244819,0.01683128,0.005081843,0.007003371,0.01187774],"category_scores_gemma":[0.3523051,0.00174261,0.001402601,0.004723269,0.08368161,0.02771049,0.02075218,0.01373565,0.001562148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01144622,"about_ca_system_score_gemma":0.00950422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002762295,"about_ca_topic_score_gemma":0.002350889,"domain_scores_codex":[0.6507431,0.2877253,0.007133225,0.01584098,0.03651946,0.002037934],"domain_scores_gemma":[0.4979355,0.4221898,0.008248473,0.05050632,0.01805967,0.003060183],"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":[0.0000325316,0.00001304905,0.0002742579,0.0002079136,0.00003454069,0.00003396014,0.002580783,0.0004824707,0.00007232927,0.9807435,0.00254732,0.01297737],"study_design_scores_gemma":[0.00002520528,0.00002120175,0.0001229798,0.0003874013,0.00001311661,0.00005905522,0.0008029905,0.001313161,0.0002104893,0.9706023,0.02641693,0.00002531397],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01127474,0.01087541,0.7119318,0.1339802,0.002944809,0.0006006628,0.0003342048,0.0003720832,0.1276861],"genre_scores_gemma":[0.55194,0.004994178,0.3882944,0.03492403,0.002188059,0.004206741,0.0002162235,0.000632657,0.01260376],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.80072,"threshold_uncertainty_score":0.9874304,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4310576792","doi":"10.1177/00491241221123088","title":"From Ends to Means: The Promise of Computational Text Analysis for Theoretically Driven Sociological Research","year":2022,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Computational and Text Analysis Methods","field":"Social Sciences","cited_by":34,"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":"Computer science; Skepticism; Field (mathematics); Relevance (law); Management science; Set (abstract data type); Computational model; Epistemology; Selection (genetic algorithm); Computational sociology; Data science; Process (computing); Sociology; Artificial intelligence; Political science","authors":[{"name":"Bart Bonikowski","is_ca":false},{"name":"Laura K. Nelson","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.4486729254285306,"gpt":0.6277772920025255,"spread":0.1791043665739949,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.04772533,0.001330582,0.001562148,0.00736503,0.004788702,0.02512696,0.004063154,0.003994727,0.0109742],"category_scores_gemma":[0.1537814,0.0009345489,0.001510869,0.006246351,0.02453191,0.04640342,0.01169228,0.008966723,0.002558948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003286366,"about_ca_system_score_gemma":0.005334416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001173181,"about_ca_topic_score_gemma":0.002003332,"domain_scores_codex":[0.9519697,0.04001203,0.001231462,0.001897996,0.004534476,0.0003542927],"domain_scores_gemma":[0.6421149,0.3278784,0.004716418,0.01919315,0.004580602,0.001516587],"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":[0.00005955173,0.00004108351,0.001059392,0.000638399,0.00005951426,0.00009275677,0.00741728,0.001577698,0.0003419457,0.9248182,0.009976122,0.05391802],"study_design_scores_gemma":[0.00001133403,0.000009916401,0.0001988179,0.0003372777,0.00001011769,0.00006134162,0.001506593,0.005324844,0.0002654535,0.9622685,0.0299725,0.00003345012],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0111026,0.009592866,0.8501857,0.07957366,0.001622943,0.0003965491,0.0006504717,0.0006972714,0.04617798],"genre_scores_gemma":[0.19834,0.009189635,0.7763157,0.005223824,0.002626496,0.001661489,0.0007865609,0.0008063406,0.005049944],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9522747,"threshold_uncertainty_score":0.2523987,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2812371591","doi":"10.1177/0049124118782554","title":"Perceived Corruption, Trust, and Interviewer Behavior in 26 European Countries","year":2018,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Corruption and Economic Development","field":"Social Sciences","cited_by":31,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Dalhousie University","funders":"","keywords":"Interview; European Social Survey; Deviance (statistics); Language change; Psychology; Social psychology; Survey research; Variation (astronomy); Criminology; Political science; Applied psychology; Statistics; Law","authors":[{"name":"Jörg Blasius","is_ca":false},{"name":"Victor Thiessen","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3278645290472383,"gpt":0.5547942230466409,"spread":0.2269296939994026,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009903182,0.000246573,0.0003659225,0.001332302,0.0006448237,0.001129062,0.000265416,0.000546234,0.0008061467],"category_scores_gemma":[0.0136869,0.0003175364,0.0002514885,0.001864971,0.001130343,0.0005589816,0.001322896,0.0004564634,0.0001237587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009700467,"about_ca_system_score_gemma":0.0005223003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01104136,"about_ca_topic_score_gemma":0.0110597,"domain_scores_codex":[0.9929027,0.005621979,0.0004421829,0.0003397299,0.0002437561,0.0004496376],"domain_scores_gemma":[0.9797601,0.009778025,0.007340418,0.0009258694,0.00136709,0.000828436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001682687,0.0001103457,0.9892247,0.00003991869,0.00004845461,0.0001519692,0.005299926,0.000373427,0.0001645496,0.0003087984,0.0001898481,0.003919825],"study_design_scores_gemma":[0.00001111098,0.00009404555,0.9904134,0.00005206285,0.00001661577,0.0001387544,0.007784504,0.0004741568,0.0002392033,0.00006713503,0.0006980433,0.00001109759],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993339,0.0001586039,0.00006441148,0.00003129295,0.000001554869,0.000006013932,0.00005957366,6.670031e-7,0.000343983],"genre_scores_gemma":[0.9995548,0.0001162688,0.00008607771,0.00002058317,0.000001108292,0.000007244334,0.00009458161,7.809501e-7,0.0001185877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01104136,"threshold_uncertainty_score":0.05237365,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4410554739","doi":"10.1177/00491241251339188","title":"Updating “The Future of Coding”: Qualitative Coding with Generative Large Language Models","year":2025,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Computational and Text Analysis Methods","field":"Social Sciences","cited_by":27,"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":"Russell Sage Foundation","keywords":"Coding (social sciences); Generative grammar; Computer science; Natural language processing; Linguistics; Qualitative research; Artificial intelligence; Sociology; Social science","authors":[{"name":"Nga Than","is_ca":false},{"name":"Leanne Fan","is_ca":false},{"name":"Tina Law","is_ca":false},{"name":"Laura K. Nelson","is_ca":true},{"name":"Leslie McCall","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2818745422435381,"gpt":0.6225325648240265,"spread":0.3406580225804884,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1450383,0.001423208,0.0009625413,0.004098671,0.004843164,0.01218582,0.004987217,0.002798446,0.009748672],"category_scores_gemma":[0.4446427,0.001556783,0.001525877,0.004195776,0.02694574,0.02438786,0.01067899,0.006763448,0.002623544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01021281,"about_ca_system_score_gemma":0.01473867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006793946,"about_ca_topic_score_gemma":0.008921273,"domain_scores_codex":[0.7985219,0.1782885,0.004230367,0.007846711,0.0100183,0.001094163],"domain_scores_gemma":[0.4858758,0.3883091,0.01418253,0.07850019,0.03091722,0.002215277],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001875412,0.00007070487,0.004540558,0.00127844,0.00009679854,0.0001957302,0.13612,0.006370578,0.001849917,0.7195998,0.01441154,0.1152783],"study_design_scores_gemma":[0.00007219223,0.00003979199,0.0008097984,0.001592215,0.00003738846,0.0001752657,0.01866881,0.03233928,0.002946022,0.8712533,0.07190628,0.0001596892],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01357034,0.000486505,0.9591738,0.01505915,0.0005261713,0.0005324371,0.0007495381,0.0008488533,0.009053214],"genre_scores_gemma":[0.260394,0.0005273927,0.7280648,0.003789688,0.0001945691,0.002735575,0.0007785886,0.001122387,0.002392892],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8549617,"threshold_uncertainty_score":0.767045,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2616014493","doi":"10.1177/0049124117747304","title":"Generalization of Classic Question Order Effects Across Cultures","year":2018,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Social and Intergroup Psychology","field":"Social Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Saskatchewan","funders":"Economic and Social Research Council; Danmarks Frie Forskningsfond","keywords":"Contrast (vision); Norm (philosophy); Order (exchange); Generalization; Perception; Context (archaeology); Social psychology; Psychology; Positive economics; Political science; Geography; Epistemology; Economics; Law; Computer science; Philosophy","authors":[{"name":"Tobias Stark","is_ca":false},{"name":"Henning Silber","is_ca":false},{"name":"Jon A. Krosnick","is_ca":false},{"name":"Annelies G. Blom","is_ca":false},{"name":"Midori Aoyagi","is_ca":false},{"name":"Ana Maria Belchior","is_ca":false},{"name":"Michael Bošnjak","is_ca":false},{"name":"Sanne Lund Clement","is_ca":false},{"name":"Melvin John","is_ca":false},{"name":"Guðbjörg Andrea Jónsdóttir","is_ca":false},{"name":"Karen Lawson","is_ca":true},{"name":"Peter Lynn","is_ca":false},{"name":"Johan Martinsson","is_ca":false},{"name":"Ditte Shamshiri-Petersen","is_ca":false},{"name":"Endre Tvinnereim","is_ca":false},{"name":"Ruoh‐Rong Yu","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2567032230430472,"gpt":0.6683574336594847,"spread":0.4116542106164375,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.05669145,0.0009174144,0.0007524875,0.00182103,0.000840245,0.00186319,0.001410489,0.0009998741,0.0100043],"category_scores_gemma":[0.2425707,0.0008606936,0.001565818,0.0008063913,0.003754242,0.003725195,0.005015436,0.001763888,0.000782703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008521346,"about_ca_system_score_gemma":0.0004953168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001019173,"about_ca_topic_score_gemma":0.0009186001,"domain_scores_codex":[0.9565471,0.02111583,0.003619205,0.01069507,0.007310999,0.0007118415],"domain_scores_gemma":[0.6172905,0.2673608,0.01565713,0.0855893,0.012584,0.00151832],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.009552918,0.002147485,0.45145,0.004919823,0.004834334,0.0009415295,0.03475172,0.005992073,0.0738524,0.07218107,0.005920953,0.3334557],"study_design_scores_gemma":[0.0006984168,0.003294676,0.8410628,0.0005278364,0.00129585,0.001512334,0.004684618,0.01007231,0.03730799,0.08507887,0.01415644,0.0003077128],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8364182,0.001024573,0.1071538,0.0006025984,0.0004110583,0.001429369,0.0008474974,0.0004703732,0.05164259],"genre_scores_gemma":[0.9848635,0.0001388444,0.01164422,0.0005918088,0.0001261908,0.000693728,0.000394215,0.000135731,0.001411843],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9433085,"threshold_uncertainty_score":0.2998167,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2478027989","doi":"10.1177/0049124116661575","title":"A Novel Sequential Mixed-method Technique for Contrastive Analysis of Unscripted Qualitative Data","year":2016,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Computational and Text Analysis Methods","field":"Social Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"NeuroDevNet; University of British Columbia","funders":"","keywords":"Computer science; Multimethodology; Qualitative research; Qualitative property; Subject (documents); Data science; Contrastive analysis; Psychology; Linguistics; Mathematics education; Machine learning; Sociology; World Wide Web; Social science","authors":[{"name":"Laura Y. Cabrera","is_ca":true},{"name":"Peter B. Reiner","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.6465089207335274,"gpt":0.6967122529922157,"spread":0.05020333225868834,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1107211,0.003844063,0.003013406,0.00770756,0.004106853,0.005726018,0.005496664,0.002223079,0.0242974],"category_scores_gemma":[0.2458278,0.002261039,0.003492907,0.008246874,0.00477624,0.003196929,0.006948769,0.004993264,0.00370356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004332592,"about_ca_system_score_gemma":0.007304009,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00249213,"about_ca_topic_score_gemma":0.004752346,"domain_scores_codex":[0.8098165,0.1514556,0.007825671,0.01659565,0.01314559,0.001161047],"domain_scores_gemma":[0.6839737,0.2463913,0.01374134,0.03053029,0.02414994,0.001213505],"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":[0.002671395,0.001230205,0.003924994,0.008370697,0.001672626,0.000590719,0.04234854,0.008973056,0.02556659,0.1666125,0.01472953,0.7233091],"study_design_scores_gemma":[0.004818253,0.005515394,0.01189842,0.00367811,0.001930438,0.000985616,0.01132489,0.2048148,0.06432299,0.4077209,0.2817275,0.00126266],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002956113,0.00006445442,0.9790315,0.0001399584,0.0002093292,0.01422183,0.0005015,0.0008289141,0.002046479],"genre_scores_gemma":[0.007341634,0.00002810428,0.9423391,0.0000957362,0.00003720734,0.0493578,0.0001315364,0.0002113949,0.0004575312],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8892788,"threshold_uncertainty_score":0.5855564,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3128078314","doi":"10.1177/0049124120986197","title":"Mobilizing the Masses: Measuring Resource Mobilization on Twitter","year":2021,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Social Media and Politics","field":"Social Sciences","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 Toronto","funders":"","keywords":"Measure (data warehouse); Social media; Social movement; Resource mobilization; Resource (disambiguation); Computer science; Frame (networking); Simple (philosophy); Point (geometry); Parsing; Movement (music); Lexicon; Variation (astronomy); Data science; Artificial intelligence; Political science; World Wide Web; Data mining; Mathematics; Epistemology; Politics","authors":[{"name":"Amir Abdul Reda","is_ca":false},{"name":"Semuhi Sinanoğlu","is_ca":true},{"name":"Mohamed Abdalla","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.5893974947116389,"gpt":0.6022507172952619,"spread":0.01285322258362298,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001832627,0.0003901703,0.0003252842,0.004837033,0.0007499252,0.002213527,0.000438575,0.0005515508,0.002516191],"category_scores_gemma":[0.01412563,0.0001550082,0.0002720817,0.004641465,0.001005861,0.0043399,0.00167338,0.0005395488,0.0007600312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007407477,"about_ca_system_score_gemma":0.0004446083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003725514,"about_ca_topic_score_gemma":0.005034893,"domain_scores_codex":[0.9990224,0.0004130384,0.00009368527,0.0001340782,0.0002226189,0.0001141616],"domain_scores_gemma":[0.9936461,0.003511562,0.001758885,0.0003017047,0.0004657864,0.0003159436],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002852697,0.0001572578,0.8519128,0.0004349134,0.0001865275,0.0002104101,0.01311354,0.006439832,0.005131095,0.01606441,0.006925628,0.09913832],"study_design_scores_gemma":[0.00002560433,0.0002294095,0.8421183,0.0002727081,0.0001425152,0.0002594141,0.03254895,0.06611822,0.00569414,0.01968683,0.03275271,0.0001513089],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9568514,0.0002056231,0.01268887,0.001532204,0.00005782017,0.0001408964,0.00359679,0.0002666478,0.02465969],"genre_scores_gemma":[0.993059,0.00009415749,0.004133208,0.00009190829,0.00004619465,0.0001294525,0.001467032,0.00003032647,0.0009487594],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9981674,"threshold_uncertainty_score":0.009692013,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2801448578","doi":"10.1177/0049124118769089","title":"Figure It Out!","year":2018,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Management and Organizational Studies","field":"Business, Management and Accounting","cited_by":21,"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":"Creativity; Value (mathematics); Epistemology; Sociology; Visualization; Domain (mathematical analysis); Computer science; Visual reasoning; Cognitive science; Psychology; Artificial intelligence; Social psychology; Mathematics","authors":[{"name":"Daniel Silver","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3370804006714201,"gpt":0.5101817443061937,"spread":0.1731013436347735,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001910877,0.0009617882,0.0005296849,0.001096487,0.003992263,0.008755385,0.001192525,0.002944754,0.3015866],"category_scores_gemma":[0.01052622,0.0003458948,0.0008318108,0.0007795729,0.002385374,0.01012686,0.005827676,0.004530173,0.2297755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00108566,"about_ca_system_score_gemma":0.001560324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004363331,"about_ca_topic_score_gemma":0.005404303,"domain_scores_codex":[0.9982367,0.0005828287,0.000064473,0.0003078781,0.0005832151,0.0002249031],"domain_scores_gemma":[0.9976616,0.000541098,0.0001374819,0.0004580021,0.0007373312,0.0004644719],"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":[0.00006109979,0.00002954674,0.0006472293,0.0001196668,0.00001158508,0.0002714102,0.003431307,0.00008226471,0.0005990141,0.04841958,0.8383591,0.1079682],"study_design_scores_gemma":[0.000003649207,0.00001203724,0.0002001054,0.0000740234,0.000004091898,0.0001982186,0.001408098,0.00009033187,0.0001695108,0.007225251,0.9905995,0.00001514719],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.005132167,0.003248631,0.03428899,0.109822,0.02960932,0.0002165327,0.001664225,0.009553734,0.8064645],"genre_scores_gemma":[0.04771758,0.002537781,0.02376313,0.03047572,0.002916072,0.0001973658,0.001510396,0.004332506,0.8865495],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.3015866,"threshold_uncertainty_score":0.9962019,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2792032639","doi":"10.1177/0049124117747302","title":"Optimizing Count Responses in Surveys: A Machine-learning Approach","year":2018,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":21,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; Social Science Research Institute, Duke University; University of British Columbia; University of Victoria","keywords":"Censoring (clinical trials); Count data; Poisson distribution; Computer science; Bayesian probability; Multinomial distribution; Machine learning; Statistics; Artificial intelligence; Mathematics","authors":[{"name":"Qiang Fu","is_ca":true},{"name":"Xin Guo","is_ca":false},{"name":"Kenneth C. Land","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.6338353326777821,"gpt":0.602291176727981,"spread":0.03154415594980109,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01565797,0.001161781,0.002279224,0.001931137,0.0007381362,0.001345627,0.002757507,0.002098599,0.001966983],"category_scores_gemma":[0.05148483,0.0009447563,0.001328933,0.002055735,0.001643475,0.002182085,0.002185471,0.002057486,0.0004598632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00159986,"about_ca_system_score_gemma":0.001726013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002559317,"about_ca_topic_score_gemma":0.00209059,"domain_scores_codex":[0.9868499,0.0105595,0.0003779721,0.001113612,0.0008537297,0.0002453226],"domain_scores_gemma":[0.9675589,0.0270902,0.001781939,0.001826639,0.001395924,0.0003464219],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000194806,0.0001833446,0.00485536,0.0002907224,0.0002157013,0.00006652307,0.0002144601,0.761117,0.0009189674,0.06865047,0.001770993,0.1615217],"study_design_scores_gemma":[0.00001926636,0.0000449317,0.0003299147,0.00001817406,0.00001151277,0.00001100473,0.00001740687,0.9683514,0.0003197057,0.03034217,0.0005246112,0.000009822913],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005736902,0.00009839907,0.9934266,0.0001598167,0.00001008474,0.00007439717,0.00003607238,0.0001490472,0.0003087214],"genre_scores_gemma":[0.1976903,0.0002212452,0.799514,0.0002295151,0.00008822711,0.0007534893,0.0003358338,0.00009989253,0.00106742],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.984342,"threshold_uncertainty_score":0.0828082,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2164011803","doi":"10.1177/0049124113506406","title":"Prepaid Monetary Incentives—Predictors of Taking the Money and Completing the Survey","year":2013,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Survey Methodology and Nonresponse","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Impact; Ontario Institute for Cancer Research; University of Waterloo","funders":"National Cancer Institute","keywords":"Prepayment of loan; Cash; Payment; Incentive; Survey data collection; Sample (material); Demographic economics; Survey methodology; Survey research; Actuarial science; Business; Economics; Finance; Socioeconomics; Medicine; Statistics","authors":[{"name":"Seema Mutti","is_ca":true},{"name":"Ryan David Kennedy","is_ca":true},{"name":"Mary E. Thompson","is_ca":true},{"name":"Geoffrey T. Fong","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.6779027527051609,"gpt":0.6117124448757337,"spread":0.06619030782942714,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.005066989,0.000189849,0.0002300163,0.0008350092,0.0006589106,0.001082666,0.000624684,0.0008696537,0.006375382],"category_scores_gemma":[0.03966664,0.0002496816,0.0004866591,0.001159234,0.0004224998,0.001119048,0.0008184965,0.001815794,0.000647897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003223446,"about_ca_system_score_gemma":0.001058665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007356348,"about_ca_topic_score_gemma":0.007690103,"domain_scores_codex":[0.9962158,0.002157533,0.000486941,0.0002053257,0.0005155917,0.0004188213],"domain_scores_gemma":[0.9486865,0.01631288,0.02576973,0.002288978,0.002064583,0.004877249],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001302258,0.0001291736,0.9939671,0.0000180049,0.00002660482,0.00003135612,0.0001741751,0.00008476234,0.00003841733,0.0001246994,0.0004538401,0.004821653],"study_design_scores_gemma":[0.000004604229,0.000116071,0.9979583,0.0000461996,0.00001413075,0.00008625972,0.0004883871,0.0004326353,0.0000351694,0.0001189695,0.0006927202,0.000006533054],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957072,0.0003646194,0.0003035564,0.0009718464,0.00003436054,0.00004108737,0.0006001561,0.000009176142,0.00196804],"genre_scores_gemma":[0.9984736,0.0001559793,0.0004730452,0.00007870287,0.000026718,0.00002266716,0.0002589762,0.00000504021,0.0005053788],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.994933,"threshold_uncertainty_score":0.02679712,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3134225231","doi":"10.1177/0049124121995548","title":"Marginal and Conditional Confounding Using Logits","year":2021,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"Medical Research Council; Chief Scientist Office","keywords":"Confounding; Statistics; Weighting; Econometrics; Marginal structural model; Conditional probability; Odds; Conditional probability distribution; Logistic regression; Marginal model; Inverse probability weighting; Conditional logistic regression; Mathematics; Odds ratio; Regression analysis; Medicine; Propensity score matching","authors":[{"name":"Kristian Bernt Karlson","is_ca":false},{"name":"Frank Popham","is_ca":false},{"name":"Anders Holm","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.8690128158201307,"gpt":0.7315306657257828,"spread":0.1374821500943478,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03944655,0.001413098,0.001654237,0.003247757,0.001150214,0.003988783,0.002948155,0.001518717,0.01006787],"category_scores_gemma":[0.1393063,0.0008161888,0.003102359,0.00391218,0.005469573,0.007111244,0.007903197,0.003677086,0.0008831245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001683548,"about_ca_system_score_gemma":0.002473589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002920784,"about_ca_topic_score_gemma":0.002171899,"domain_scores_codex":[0.95044,0.03730026,0.001634205,0.004655808,0.004817396,0.001152367],"domain_scores_gemma":[0.9249175,0.05919262,0.004686766,0.008261687,0.002400141,0.0005413378],"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":[0.00008242302,0.00003907731,0.006978407,0.0001966342,0.0002472562,0.000135233,0.001392737,0.009968308,0.0003002631,0.9322721,0.0009199987,0.04746747],"study_design_scores_gemma":[0.00003340876,0.00004428028,0.002463059,0.0001038041,0.0001147469,0.0001556246,0.0002211528,0.02729928,0.0005949166,0.9607235,0.008184902,0.00006130986],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01028356,0.0004660104,0.984247,0.0007622349,0.00007501829,0.00009877711,0.0002298221,0.0001628685,0.003674713],"genre_scores_gemma":[0.5143757,0.001519938,0.4727772,0.0007383485,0.0003733082,0.001469127,0.0006256878,0.0002671758,0.007853547],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9605535,"threshold_uncertainty_score":0.2086158,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2761888982","doi":"10.1177/0049124117729709","title":"Power Law Distributions and the Size Distribution of Strikes","year":2017,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Labor Movements and Unions","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Toronto","funders":"","keywords":"Log-normal distribution; Econometrics; Distribution (mathematics); Power law; Statistics; Power (physics); Perspective (graphical); Pareto distribution; Duration (music); Law; Economics; Mathematics; Political science; Physics","authors":[{"name":"Michele Campolieti","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1715518980099796,"gpt":0.5483748844190327,"spread":0.3768229864090531,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00641328,0.0003366715,0.0007162641,0.005263675,0.001595932,0.002680288,0.00237363,0.001000322,0.008643116],"category_scores_gemma":[0.07329622,0.0003964087,0.0008437809,0.007094349,0.002952432,0.001939547,0.001236274,0.001869241,0.0008837588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01572555,"about_ca_system_score_gemma":0.007815064,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.8770659,"about_ca_topic_score_gemma":0.8540026,"domain_scores_codex":[0.9941307,0.0008003371,0.000418733,0.001224797,0.002386615,0.001038843],"domain_scores_gemma":[0.9623142,0.01686444,0.009945139,0.002946983,0.006685612,0.001243594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000180304,0.00008279626,0.8745839,0.0001491678,0.0002313809,0.0003864678,0.006649873,0.02359104,0.0003854773,0.03918507,0.009155848,0.04541866],"study_design_scores_gemma":[0.00002994471,0.00006201038,0.9383823,0.0001053286,0.00004720512,0.0002223988,0.004988285,0.02939938,0.0002937013,0.01214116,0.01423502,0.00009325129],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9477399,0.001336393,0.01588215,0.001950764,0.00006389579,0.0002014477,0.009831344,0.0001987542,0.02279541],"genre_scores_gemma":[0.9912593,0.0003760098,0.001549856,0.00006520929,0.00001882936,0.00003476841,0.003219311,0.00003753582,0.00343925],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8770659,"threshold_uncertainty_score":0.2473161,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3019463389","doi":"10.1177/0049124120914928","title":"Joint Modeling of Multivariate Survival Data With an Application to Retirement","year":2020,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University; University of Victoria","funders":"","keywords":"Univariate; Multivariate statistics; Proportional hazards model; Covariate; Event (particle physics); Econometrics; Survival analysis; Variety (cybernetics); Multivariate analysis; Event data; Computer science; Statistics; Actuarial science; Psychology; Mathematics; Economics","authors":[{"name":"Grace Li","is_ca":true},{"name":"Mary Lesperance","is_ca":true},{"name":"Zheng Wu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.5795516871879395,"gpt":0.581134355203404,"spread":0.001582668015464472,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01437444,0.001114442,0.001575008,0.001691499,0.0006326655,0.001746227,0.002219992,0.001442082,0.003242206],"category_scores_gemma":[0.02829231,0.0008581059,0.002840052,0.002758502,0.001564466,0.001876192,0.003136531,0.002858595,0.0004343271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001130083,"about_ca_system_score_gemma":0.00206888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01399025,"about_ca_topic_score_gemma":0.01106512,"domain_scores_codex":[0.9940414,0.004384404,0.0002304405,0.0005604896,0.0005231946,0.0002600857],"domain_scores_gemma":[0.9750718,0.02008905,0.002134096,0.001421893,0.0009040693,0.0003790628],"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":[0.000142975,0.0001228144,0.01418383,0.000189425,0.0004386548,0.0003253473,0.0007074147,0.5834932,0.0004669011,0.3442662,0.002211859,0.0534514],"study_design_scores_gemma":[0.00001469581,0.00007230644,0.001541074,0.00002801819,0.00004562824,0.00006365492,0.00006115787,0.9151382,0.0001000944,0.08077292,0.002130291,0.00003184369],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01101257,0.0005688522,0.9866693,0.0006319026,0.00006487701,0.00005131685,0.0002252047,0.0001925301,0.0005834133],"genre_scores_gemma":[0.5163275,0.002970343,0.4673603,0.0003355533,0.0005872263,0.0009236614,0.00110031,0.0002443914,0.01015078],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01437444,"threshold_uncertainty_score":0.07602018,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2888408547","doi":"10.1177/0049124118782550","title":"Analyzing Heaped Counts Versus Longitudinal Presence/Absence Data in Joint Zero-inflated Discrete Regression Models","year":2018,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Count data; Statistics; Outcome (game theory); Event (particle physics); Regression analysis; Event data; Econometrics; Mathematics; Rounding; Psychology; Computer science; Covariate","authors":[{"name":"Erin R. Lundy","is_ca":true},{"name":"C. B. Dean","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.6965302466042542,"gpt":0.6410708432010603,"spread":0.05545940340319389,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05665371,0.001264532,0.002335288,0.002348487,0.0008260561,0.003278662,0.00355806,0.002276239,0.002474712],"category_scores_gemma":[0.1511908,0.0008691649,0.002239135,0.003569452,0.003414427,0.00345659,0.004141822,0.003167249,0.0005099849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009927006,"about_ca_system_score_gemma":0.0014161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006270826,"about_ca_topic_score_gemma":0.003740364,"domain_scores_codex":[0.9562864,0.03511801,0.001654483,0.004350992,0.001557619,0.00103257],"domain_scores_gemma":[0.7450323,0.2165372,0.01696985,0.01779894,0.00273428,0.0009275294],"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":[0.001225826,0.0005845029,0.1988495,0.0008886919,0.002676921,0.001449824,0.003421267,0.4067429,0.001767784,0.2257607,0.002828098,0.153804],"study_design_scores_gemma":[0.00005537358,0.0003422869,0.01727847,0.0001741408,0.0003786011,0.0002294773,0.0004562824,0.8596755,0.0009085165,0.1177816,0.002610091,0.0001097007],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1554645,0.0008862998,0.8406141,0.0008993739,0.00009599224,0.0001208853,0.0008469505,0.0003476957,0.0007240946],"genre_scores_gemma":[0.8060508,0.0006971036,0.1882671,0.000241289,0.0002537438,0.0004948232,0.001535301,0.0001080848,0.00235176],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05665371,"threshold_uncertainty_score":0.2996171,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3129011248","doi":"10.1177/0049124120986192","title":"A New Methodological Approach to Study Household Structure From Census and Survey Data","year":2021,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Quebec Statistical Institute; Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Census; Indigenous; Representation (politics); Survey data collection; Current Population Survey; Population; Survey methodology; Yield (engineering); Econometrics; Geography; Computer science; Regional science; Data science; Sociology; Statistics; Demography; Mathematics; Political science","authors":[{"name":"Simona Bignami","is_ca":true},{"name":"Virginie Boulet","is_ca":true},{"name":"Charles-Olivier Simard","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.890380508101297,"gpt":0.6410469044849224,"spread":0.2493336036163746,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01724975,0.0006703821,0.0008508851,0.007465242,0.001743978,0.002618158,0.002300503,0.000820934,0.003112961],"category_scores_gemma":[0.05292917,0.0006209056,0.001168082,0.0155818,0.002839921,0.00395013,0.004415336,0.00246168,0.0006691508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002371926,"about_ca_system_score_gemma":0.004069212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009643129,"about_ca_topic_score_gemma":0.009739916,"domain_scores_codex":[0.9703353,0.02150419,0.001401545,0.002640164,0.003790545,0.0003284029],"domain_scores_gemma":[0.9767531,0.01211308,0.002798445,0.005120548,0.002821563,0.0003932086],"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":[0.00006737757,0.0001136246,0.03645867,0.0006687405,0.0005049696,0.0001732537,0.006136375,0.00706507,0.001344306,0.7244129,0.00974309,0.2133116],"study_design_scores_gemma":[0.000130241,0.0003943368,0.04893386,0.0008758503,0.0002650167,0.0009940844,0.006093342,0.03648943,0.001784697,0.7351304,0.168663,0.0002457202],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008896163,0.000488548,0.9824418,0.001113853,0.000194921,0.0006273082,0.00109848,0.0001379032,0.005001093],"genre_scores_gemma":[0.1636026,0.001183261,0.824136,0.001018759,0.0003651621,0.004520511,0.002541968,0.0001561832,0.002475627],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01724975,"threshold_uncertainty_score":0.09122646,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4401031998","doi":"10.1177/00491241241266634","title":"Promises and Limits of Using Targeted Social Media Advertising to Sample Global Migrant Populations: Nigerians at Home and Abroad","year":2024,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Migration, Ethnicity, and Economy","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Saint Mary's University; McGill University","funders":"Social Sciences and Humanities Research Council of Canada; Canada Research Chairs","keywords":"Nigerians; Sample (material); Advertising; Social media; Media use; Sociology; Demographic economics; Political science; Business; Psychology; Economics; Social psychology","authors":[{"name":"Thomas Soehl","is_ca":true},{"name":"Zhenxiang Chen","is_ca":true},{"name":"Aaron Erlich","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3341095454652583,"gpt":0.5486357934169476,"spread":0.2145262479516892,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1557482,0.001140806,0.001092889,0.003018387,0.00332477,0.005857944,0.003921836,0.00298465,0.003692142],"category_scores_gemma":[0.2300062,0.001083998,0.0008766154,0.004077933,0.004293578,0.007648356,0.007000145,0.00292648,0.001473937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001901849,"about_ca_system_score_gemma":0.00469576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02243518,"about_ca_topic_score_gemma":0.04297769,"domain_scores_codex":[0.8853523,0.09559164,0.005200182,0.003678456,0.008042148,0.002135398],"domain_scores_gemma":[0.7787584,0.1355161,0.02061597,0.03091919,0.02907034,0.00511995],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008481937,0.0007026303,0.6001562,0.003529452,0.0007946346,0.000595957,0.06604451,0.001664348,0.002211712,0.01844881,0.01696486,0.2880387],"study_design_scores_gemma":[0.0002169786,0.003204093,0.6563122,0.01635376,0.0008282959,0.001779138,0.1128941,0.007560051,0.006825458,0.05115543,0.1424476,0.0004229179],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7260702,0.02235144,0.07653853,0.07885983,0.003338902,0.006232582,0.00775291,0.0002493959,0.07860624],"genre_scores_gemma":[0.8587576,0.007621503,0.09327792,0.01886975,0.00121875,0.01307567,0.001932047,0.0001274426,0.005119285],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8442518,"threshold_uncertainty_score":0.8236852,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4380046704","doi":"10.1177/00491241231176845","title":"Lagged Dependent Variable Predictors, Classical Measurement Error, and Path Dependency: The Conditions Under Which Various Estimators are Appropriate","year":2023,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"School Choice and Performance","field":"Social Sciences","cited_by":5,"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":"Estimator; Instrumental variable; Ordinary least squares; Statistics; Mathematics; Invariant estimator; Econometrics; Efficient estimator; Standard error; Least-squares function approximation; Consistency (knowledge bases); Minimum-variance unbiased estimator","authors":[{"name":"Anders Holm","is_ca":true},{"name":"Anders Hjorth‐Trolle","is_ca":false},{"name":"Robert Andersen","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2884929320831218,"gpt":0.5023517921103442,"spread":0.2138588600272224,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.07060649,0.000997104,0.001924164,0.002387202,0.00089555,0.00301331,0.002561546,0.002695458,0.004743471],"category_scores_gemma":[0.2758977,0.0007861205,0.00195758,0.00493836,0.00283975,0.006482389,0.00271871,0.003180226,0.0007859977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001068749,"about_ca_system_score_gemma":0.002267418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00246562,"about_ca_topic_score_gemma":0.002342647,"domain_scores_codex":[0.9681563,0.02451546,0.001721352,0.002813256,0.002236035,0.0005574952],"domain_scores_gemma":[0.7652132,0.2028863,0.01309817,0.01170413,0.006460655,0.0006375696],"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":[0.0004384833,0.000158855,0.1009375,0.00163679,0.001345365,0.0005941179,0.001209827,0.05513016,0.001078474,0.5495802,0.008785604,0.2791047],"study_design_scores_gemma":[0.0002477777,0.0005030276,0.04689528,0.001962217,0.0007652249,0.0009284095,0.001247435,0.3287949,0.004437915,0.5875527,0.02639584,0.0002692781],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02833381,0.004313741,0.9608443,0.002583698,0.0003440955,0.0002061882,0.0006708429,0.0002336013,0.00246975],"genre_scores_gemma":[0.4519311,0.005966363,0.5325083,0.001437623,0.0009763739,0.001343829,0.001837593,0.0002876149,0.003711275],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9293935,"threshold_uncertainty_score":0.3734072,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4290613457","doi":"10.1177/00491241221113877","title":"The Design and Optimality of Survey Counts: A Unified Framework Via the Fisher Information Maximizer","year":2022,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Hong Kong Polytechnic University","keywords":"Fisher information; Range (aeronautics); Mathematics; Statistics; Generalized linear model; Computer science; Econometrics; Optimal design; Mathematical optimization","authors":[{"name":"Xin Guo","is_ca":false},{"name":"Qiang Fu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.6171696352915063,"gpt":0.5685923866874328,"spread":0.04857724860407342,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02692207,0.001179439,0.002167879,0.001962848,0.0006000212,0.00152394,0.002467366,0.001891285,0.002044768],"category_scores_gemma":[0.07962035,0.001180399,0.001163206,0.001882937,0.003162554,0.003941749,0.002469676,0.002080354,0.0004683723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001553964,"about_ca_system_score_gemma":0.00259327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001363616,"about_ca_topic_score_gemma":0.0009023899,"domain_scores_codex":[0.9711901,0.023367,0.0007485657,0.001762778,0.002484936,0.000446473],"domain_scores_gemma":[0.9619468,0.03033881,0.002785055,0.002353963,0.00217193,0.0004034313],"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":[0.0001529318,0.00009396238,0.003027515,0.0003486581,0.0001092298,0.00006530719,0.0004297791,0.3162465,0.001739083,0.5504649,0.001360617,0.1259615],"study_design_scores_gemma":[0.00006268603,0.0002704497,0.00100829,0.000083789,0.00003692073,0.00005359366,0.00006358059,0.7786613,0.001224759,0.2154366,0.003053206,0.00004487897],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00203174,0.00007027551,0.9974678,0.00007934656,0.000005658529,0.00003633132,0.00001381361,0.00003239186,0.0002627997],"genre_scores_gemma":[0.09819544,0.0003537637,0.8997172,0.00009030764,0.00006024535,0.0006503642,0.00008905087,0.00006642441,0.0007773057],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02692207,"threshold_uncertainty_score":0.1423792,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4386245620","doi":"10.1177/00491241231192383","title":"Comparing Methods for Estimating Demographics in Racially Polarized Voting Analyses","year":2023,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Electoral Systems and Political Participation","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Geocoding; Voting; Turnout; Bayesian probability; Demographics; Population; Race (biology); Econometrics; Inference; Causal inference; Statistics; Geography; Demography; Computer science; Political science; Mathematics; Sociology; Cartography; Artificial intelligence; Politics","authors":[{"name":"Ari Decter-Frain","is_ca":false},{"name":"Pratik Sachdeva","is_ca":false},{"name":"Loren Collingwood","is_ca":false},{"name":"Hikari Murayama","is_ca":false},{"name":"Juandalyn Burke","is_ca":false},{"name":"Matt A. Barreto","is_ca":false},{"name":"Scott Henderson","is_ca":false},{"name":"Spencer A. Wood","is_ca":false},{"name":"Joshua Zingher","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.7717421973928245,"gpt":0.7209083247582806,"spread":0.05083387263454386,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1480835,0.001161111,0.001103495,0.004618668,0.001529442,0.003858033,0.002301431,0.002048929,0.001965012],"category_scores_gemma":[0.3503406,0.0009888592,0.00232659,0.004267243,0.002513563,0.00360858,0.004761523,0.002940371,0.0006880029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002007697,"about_ca_system_score_gemma":0.002666816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0113165,"about_ca_topic_score_gemma":0.01921671,"domain_scores_codex":[0.8444048,0.1382322,0.003420147,0.005785769,0.007171215,0.0009859718],"domain_scores_gemma":[0.6107814,0.3412221,0.008460569,0.02464693,0.01382235,0.001066696],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002324078,0.000462497,0.4159996,0.001416123,0.008436647,0.0001537481,0.01044007,0.1058734,0.00341927,0.1162401,0.006873025,0.3283614],"study_design_scores_gemma":[0.0005454969,0.0009419334,0.159776,0.001187279,0.001483668,0.0005227454,0.006313585,0.5765898,0.008055346,0.2217661,0.02231216,0.0005060065],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1978947,0.001999301,0.789313,0.001814753,0.0002833512,0.0008117433,0.001177937,0.0004812493,0.006224059],"genre_scores_gemma":[0.4864182,0.0006332741,0.5077069,0.0005956638,0.0001182764,0.001363593,0.001490867,0.0004414772,0.001231761],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1480835,"threshold_uncertainty_score":0.7831496,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3015404063","doi":"10.1177/0049124120914943","title":"Clustered Iconography: A Resurrected Method for Representing Multidimensional Data","year":2020,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval","funders":"","keywords":"Iconography; Computer science; Presentation (obstetrics); Data science; Data mining; Information retrieval; History; Archaeology","authors":[{"name":"Olav Muurlink","is_ca":false},{"name":"Anthony M. Gould","is_ca":true},{"name":"Jean‐Etienne Joullié","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.6367181529069946,"gpt":0.6249219023411513,"spread":0.01179625056584332,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0118819,0.002209104,0.001281237,0.01431681,0.00259281,0.01099567,0.002890246,0.002295678,0.0305671],"category_scores_gemma":[0.06899707,0.001042243,0.002107301,0.01312501,0.005705713,0.008629741,0.007098425,0.004451204,0.006881297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001955846,"about_ca_system_score_gemma":0.004894787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004343776,"about_ca_topic_score_gemma":0.005952127,"domain_scores_codex":[0.9887246,0.006760079,0.0007585149,0.001238661,0.002219331,0.0002988487],"domain_scores_gemma":[0.9450216,0.03458175,0.002881652,0.01028196,0.006241566,0.0009915698],"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":[0.0002128171,0.00005661734,0.002072135,0.001759479,0.0001952407,0.0004132881,0.01295937,0.005811946,0.004163193,0.5219488,0.08238395,0.3680232],"study_design_scores_gemma":[0.00009949086,0.0001132874,0.001786468,0.001255163,0.0001374711,0.001138307,0.004382394,0.04635611,0.006088983,0.482242,0.456045,0.0003552107],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001971293,0.0006719152,0.9798194,0.001734553,0.0006900296,0.0002999193,0.001531864,0.004319058,0.00896195],"genre_scores_gemma":[0.04782965,0.001228862,0.9369841,0.0008851124,0.0006172469,0.001345222,0.00173601,0.003112068,0.006261754],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0305671,"threshold_uncertainty_score":0.1022572,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4200319388","doi":"10.1177/00491241211067514","title":"And the Rest is History: Measuring the Scope and Recall of Wikipedia’s Coverage of Three Women’s Movement Subgroups","year":2021,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Wikis in Education and Collaboration","field":"Social 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":"University of British Columbia","funders":"","keywords":"Scope (computer science); Recall; Typology; Phrase; Operationalization; Movement (music); Comparative historical research; Categorical variable; Historical method; Computer science; Sociology; Epistemology; History; Social science; Cognitive psychology; Psychology; Natural language processing; Aesthetics","authors":[{"name":"Laura K. Nelson","is_ca":true},{"name":"Rebekah Getman","is_ca":false},{"name":"Syed Arefinul Haque","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.255754211112796,"gpt":0.4841200688200403,"spread":0.2283658577072443,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.00770659,0.0003021017,0.0002873347,0.01257162,0.0009111293,0.002043892,0.0006269463,0.0006184098,0.001144546],"category_scores_gemma":[0.08425429,0.0001548829,0.0002531431,0.007307498,0.001183478,0.005032942,0.002093933,0.0005074418,0.0003059711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006757694,"about_ca_system_score_gemma":0.0005530065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005393009,"about_ca_topic_score_gemma":0.007578084,"domain_scores_codex":[0.9966649,0.001215357,0.0007062005,0.000523833,0.0007403035,0.0001493041],"domain_scores_gemma":[0.8931941,0.06721991,0.02103549,0.005622918,0.01152501,0.001402651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003912618,0.00009922476,0.7908565,0.001249808,0.0002648162,0.0002198255,0.08990001,0.0007096851,0.003589406,0.002191836,0.002603045,0.1079245],"study_design_scores_gemma":[0.00001026237,0.0003026608,0.9011387,0.0005992206,0.0001893518,0.000620309,0.06362583,0.002556606,0.004886172,0.002046462,0.02394556,0.00007889172],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9864478,0.0008322601,0.00254633,0.0002099632,0.00002402407,0.00007153906,0.002805517,0.00004627555,0.007016321],"genre_scores_gemma":[0.9901252,0.0004428879,0.004401714,0.00005370843,0.00005058757,0.0001596429,0.003442184,0.00003455544,0.001289336],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9874284,"threshold_uncertainty_score":0.04075688,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4407112381","doi":"10.1177/00491241251314039","title":"When to Use Counterfactuals in Causal Historiography: Methods for Semantics and Inference","year":2025,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Qualitative Comparative Analysis Research","field":"Social 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":"McGill University","funders":"","keywords":"Counterfactual conditional; Causal inference; Historiography; Semantics (computer science); Inference; Econometrics; Computer science; Causal model; Epistemology; Linguistics; Counterfactual thinking; Statistics; Artificial intelligence; Mathematics; Programming language; Political science; Philosophy; Law","authors":[{"name":"Tay Jeong","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.6295248969421484,"gpt":0.7249763478686025,"spread":0.09545145092645413,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.08119246,0.001706522,0.00274406,0.006991179,0.003778268,0.0162418,0.004791467,0.006171463,0.00907598],"category_scores_gemma":[0.163652,0.001673519,0.00391887,0.005831581,0.03808301,0.04498398,0.007696656,0.01294754,0.002080783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004254886,"about_ca_system_score_gemma":0.003492439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00416966,"about_ca_topic_score_gemma":0.003010889,"domain_scores_codex":[0.9536776,0.03759045,0.002053573,0.003077615,0.002957572,0.000643264],"domain_scores_gemma":[0.8723138,0.1020646,0.003786734,0.01739892,0.003405042,0.001030926],"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":[0.00001844881,0.00001401801,0.0002719062,0.00007597339,0.00003543768,0.00003938494,0.001704005,0.0007761926,0.00005425246,0.9837054,0.0008125997,0.01249233],"study_design_scores_gemma":[0.00001118737,0.000003384765,0.00002926873,0.00007249408,0.000007840657,0.00001954735,0.0002074922,0.002248115,0.0001146478,0.9924808,0.004793994,0.00001119898],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002917049,0.002447243,0.9737489,0.01083112,0.0003693785,0.0001560412,0.0001495202,0.0003135939,0.009067169],"genre_scores_gemma":[0.1785721,0.002060306,0.8114648,0.001890056,0.0006020837,0.001307611,0.0002654868,0.0005520952,0.003285581],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9188075,"threshold_uncertainty_score":0.4293919,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4414803296","doi":"10.1177/00491241251358895","title":"Beyond the Diagonal Reference Model: Critiques and New Directions in the Analysis of Mobility Effects","year":2025,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Intergenerational and Educational Inequality Studies","field":"Social Sciences","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","funders":"","keywords":"Identification (biology); Diagonal; Bounding overwatch; Sign (mathematics); Social mobility; Mobility model","authors":[{"name":"Ethan Fosse","is_ca":true},{"name":"Fabian T. Pfeffer","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.4698768722309694,"gpt":0.6426193233113723,"spread":0.1727424510804029,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06010138,0.001673936,0.003503609,0.004219245,0.001903429,0.005720193,0.009335022,0.004152445,0.01028775],"category_scores_gemma":[0.1450404,0.001111153,0.003687888,0.005639336,0.01872407,0.01335352,0.006481031,0.0101328,0.002038119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004220331,"about_ca_system_score_gemma":0.003940622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01199046,"about_ca_topic_score_gemma":0.006926416,"domain_scores_codex":[0.958721,0.02929891,0.001538209,0.003785439,0.006032183,0.0006243452],"domain_scores_gemma":[0.8102613,0.1689346,0.004500666,0.01078997,0.00472195,0.0007915908],"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":[0.000006641344,0.00001685698,0.000532131,0.0001217133,0.00004195069,0.00003397261,0.0002972134,0.002500405,0.00001461928,0.9846722,0.001669335,0.01009297],"study_design_scores_gemma":[0.000008037627,0.000009325571,0.0002341147,0.00009976585,0.0000115864,0.00002520735,0.0001323248,0.0101963,0.00003161257,0.9837514,0.005489936,0.00001038241],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006462175,0.01090298,0.9031532,0.05359549,0.0006025928,0.000095109,0.0004152072,0.000279276,0.02449397],"genre_scores_gemma":[0.5929927,0.02716975,0.3361018,0.01642413,0.006359349,0.001341497,0.0007576253,0.0008215134,0.01803168],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06010138,"threshold_uncertainty_score":0.3178502,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4210865241","doi":"10.1177/00491241221077238","title":"Comparing Single- and Multiple-Question Designs of Measuring Family Income in China Family Panel Studies","year":2022,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Econometrics; Percentile; Economics; Contrast (vision); Quarter (Canadian coin); Demographic economics; Statistics; Mathematics; Geography; Computer science","authors":[{"name":"Qiong Wu","is_ca":false},{"name":"Liping Gu","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.9006386086819724,"gpt":0.6303685016720665,"spread":0.2702701070099059,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.159804,0.0008911751,0.001144881,0.002455997,0.002017855,0.002011624,0.002622995,0.001278026,0.002670348],"category_scores_gemma":[0.2250959,0.0007828749,0.002577941,0.004258516,0.001675186,0.002329743,0.002671378,0.001442835,0.0002685678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002944183,"about_ca_system_score_gemma":0.002727409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01759659,"about_ca_topic_score_gemma":0.01509308,"domain_scores_codex":[0.7831442,0.1953068,0.00516147,0.007446916,0.007472895,0.001467722],"domain_scores_gemma":[0.7704344,0.1608386,0.02451498,0.02889454,0.01407088,0.001246573],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001679827,0.0004929083,0.8352543,0.001413886,0.008655394,0.0002392373,0.009188066,0.01158887,0.0008533765,0.01928217,0.003442283,0.1079098],"study_design_scores_gemma":[0.001025004,0.002054366,0.8716522,0.0009494184,0.003895471,0.0001865355,0.005526538,0.0739582,0.00359426,0.02503012,0.01184139,0.0002865884],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8051568,0.003310576,0.1798052,0.001427924,0.0004422917,0.003071747,0.00230871,0.0001536663,0.004323143],"genre_scores_gemma":[0.9478622,0.0005484573,0.04320765,0.0004099544,0.0001138288,0.005896637,0.001279796,0.00002974728,0.0006517869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.840196,"threshold_uncertainty_score":0.8451344,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}