{"id":"W3161098474","doi":"10.36834/cmej.71053","title":"The ongoing need for feminism in medicine","year":2020,"lang":"en","type":"article","venue":"Canadian Medical Education Journal","topic":"Diversity and Career in Medicine","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Feminism; Data science; Computer science; Political science; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02249507,0.0005749749,0.00126068,0.002338493,0.02830317,0.0171385,0.002700462,0.015468,0.02908902],"category_scores_gemma":[0.02395394,0.0005326747,0.0006216422,0.002682518,0.06474623,0.01036191,0.01055482,0.01834038,0.001636826],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05206496,"about_ca_system_score_gemma":0.1265587,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3868603,"about_ca_topic_score_gemma":0.6200848,"domain_scores_codex":[0.9863869,0.004887441,0.0002793176,0.000923735,0.003574913,0.003947837],"domain_scores_gemma":[0.9486104,0.02380234,0.001727111,0.0009339252,0.00595398,0.0189723],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005246869,0.00004329301,0.001066557,0.0005082286,0.00001621184,0.0003070682,0.02471215,0.0001008397,0.0002737434,0.6603733,0.256088,0.05645816],"study_design_scores_gemma":[0.00002925488,0.00002157904,0.001666717,0.0007400963,0.000007747788,0.0001568495,0.02448219,0.00006087822,0.00009237288,0.08781009,0.8848883,0.00004413456],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.002473467,0.01839993,0.0002759224,0.9371901,0.004349883,0.000008679662,0.00004089768,0.00001705428,0.03724411],"genre_scores_gemma":[0.3780965,0.04561413,0.002689266,0.5153407,0.0168061,0.00009982424,0.0000899873,0.0001519217,0.04111153],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9775049,"threshold_uncertainty_score":0.769217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03786492765845016,"score_gpt":0.3386448297776283,"score_spread":0.3007799021191782,"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."}}