{"id":"W4318539527","doi":"10.32920/21979703.v1","title":"Advancing women in science, medicine and global health","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Global Health and Surgery","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Health science; New delhi; Center (category theory); Library science; Political science; Sociology; Media studies; Medicine; Gerontology; Medical education; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004524445,0.0002023712,0.0008622798,0.0004386416,0.00008694825,0.0000131738,0.000114443,0.0001331385,0.0000697295],"category_scores_gemma":[0.0009951979,0.000156359,0.00002962947,0.000977475,0.000343434,0.00004262645,0.0004514458,0.0004453363,0.00002253325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002467812,"about_ca_system_score_gemma":0.004673772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005888022,"about_ca_topic_score_gemma":0.0008695667,"domain_scores_codex":[0.9967503,0.00003921367,0.0005922618,0.0006343221,0.000576101,0.001407787],"domain_scores_gemma":[0.9978381,0.00008634666,0.0001200803,0.0003651608,0.00009524917,0.001494996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004421894,0.0001822396,0.8154017,0.007227796,0.00003491828,0.0005057234,0.003575487,0.00005307899,0.00002193439,0.006060953,0.07398126,0.0925127],"study_design_scores_gemma":[0.001977001,0.0005551856,0.9519231,0.003698539,0.00001044372,0.0001165459,0.00364094,0.00105409,0.000001956313,0.02443958,0.01228636,0.0002961986],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9108265,0.002648313,0.0001031853,0.05886788,0.002189287,0.0009757345,0.0000236601,0.0002677425,0.02409771],"genre_scores_gemma":[0.9792693,0.002920194,0.0007956206,0.01540257,0.000313754,0.00005770055,0.00003081283,0.00001831561,0.001191788],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1365214,"threshold_uncertainty_score":0.8900967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03398801824038523,"score_gpt":0.4011922315395198,"score_spread":0.3672042132991346,"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."}}