{"id":"W4398624520","doi":"10.7910/dvn/pl2xfd/d2eu2p","title":"EES_gender_knowledge_ajpsreplication.tab","year":2017,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Gender Politics and Representation","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Socialization; Term (time); Replication (statistics); Politics; Representation (politics); Psychology; Political socialization; Social psychology; Political science; American political science; Mathematics; Statistics; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001283403,0.002414917,0.001257481,0.005174796,0.001363116,0.004049633,0.003141654,0.002473947,0.1772594],"category_scores_gemma":[0.006338107,0.0007366096,0.001348558,0.008604363,0.0007485368,0.002387991,0.003485262,0.001821769,0.1749866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002092807,"about_ca_system_score_gemma":0.003202139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02780535,"about_ca_topic_score_gemma":0.04713124,"domain_scores_codex":[0.9988851,0.0001890789,0.000100933,0.0002980999,0.0002638946,0.0002628308],"domain_scores_gemma":[0.9975619,0.0006619527,0.0002143336,0.0007091337,0.0005061825,0.0003464427],"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":[0.00002602498,0.00001182788,0.000421316,0.0003513618,0.00001306671,0.00001119814,0.00003309315,0.00007738077,0.00005851533,0.0005945448,0.9968292,0.001572552],"study_design_scores_gemma":[0.00011242,0.000008569535,0.001803263,0.0002255795,0.00001476692,0.00003542896,0.0001373848,0.0002210782,0.000328914,0.00119739,0.9958936,0.00002164461],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001237336,0.00006638049,0.00004958761,0.00009772703,0.00003325597,0.000007419214,0.9978702,0.0004304653,0.001321207],"genre_scores_gemma":[0.0006775037,0.00009801592,0.0002368112,0.00008530043,0.00001502035,0.00007109753,0.9973632,0.0001573692,0.001295769],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1772594,"threshold_uncertainty_score":0.5929919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05475347118879271,"score_gpt":0.3627474558431805,"score_spread":0.3079939846543878,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}