{"id":"W3192228297","doi":"10.3390/vetsci8080159","title":"Women Representation and Gender Equality in Different Academic Levels in Veterinary Science","year":2021,"lang":"en","type":"article","venue":"Veterinary Sciences","topic":"Veterinary Practice and Education Studies","field":"Health Professions","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Staffing; Accreditation; Gender disparity; Inequality; Gender equality; Distribution (mathematics); Gender bias; Veterinary medicine; Political science; Medical education; Medicine; Demography; Sociology; Psychology; Gender studies; Nursing","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":[0.003168818,0.0001552372,0.0002713418,0.0004833296,0.0009411413,0.00004283273,0.0002908685,0.00008696863,0.0002341499],"category_scores_gemma":[0.0007319858,0.0001322671,0.00001924233,0.001804948,0.000694063,0.00132809,0.0007136674,0.0004917822,0.00003601362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003028756,"about_ca_system_score_gemma":0.0007313723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001171093,"about_ca_topic_score_gemma":0.00001424803,"domain_scores_codex":[0.9966434,0.0009537576,0.000550653,0.0006983956,0.0004238233,0.0007299989],"domain_scores_gemma":[0.9985873,0.0007780007,0.0001659166,0.00025477,0.00008332155,0.0001307029],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001631484,0.0002321665,0.6859391,0.0003347123,0.0000091784,0.0002402552,0.1027223,0.00001738078,0.2029133,0.001635888,0.0001278011,0.005664776],"study_design_scores_gemma":[0.0003985239,0.0004726092,0.9318696,0.00009427332,0.000002050636,0.0001022655,0.06265926,0.0001112549,0.00007175023,0.002143266,0.001913023,0.0001621746],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921984,0.0004266043,0.00001483193,0.001816283,0.0008692417,0.0002445891,0.000005505847,0.00002763813,0.004396927],"genre_scores_gemma":[0.9978732,0.0004031151,0.0003697768,0.0006273881,0.00008977784,0.0001476994,0.000001544288,0.000006178174,0.0004813381],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2459305,"threshold_uncertainty_score":0.7238593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7650100813298905,"score_gpt":0.6074062185928815,"score_spread":0.157603862737009,"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."}}