{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002178088,0.0001195174,0.0002904794,0.001122175,0.001470431,0.001590587,0.0002935757,0.0003168698,0.006429159],"category_scores_gemma":[0.005584711,0.0001049791,0.0002065097,0.001056963,0.001621344,0.0009748098,0.001481753,0.0004576297,0.0004028156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001235634,"about_ca_system_score_gemma":0.001613701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02129104,"about_ca_topic_score_gemma":0.05249956,"domain_scores_codex":[0.9980236,0.0006732904,0.0000734864,0.0001581083,0.0004643046,0.0006070844],"domain_scores_gemma":[0.997537,0.0008526764,0.0007517574,0.00006722998,0.0002690562,0.0005222225],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002206588,0.00007894952,0.911481,0.00009289176,0.00003499504,0.0003659416,0.04109234,0.0000652076,0.0007068464,0.004075971,0.00113081,0.04065445],"study_design_scores_gemma":[0.000004685674,0.0001236545,0.9357703,0.0001445242,0.00001285887,0.000353993,0.05662768,0.0001139098,0.0001692757,0.001146384,0.005519349,0.00001339697],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905939,0.001151965,0.0001768564,0.0009959557,0.00003318627,0.000007725541,0.00006210705,0.000001757244,0.006976504],"genre_scores_gemma":[0.9988053,0.0001929206,0.00003382807,0.00007919817,0.00001031697,0.000002614044,0.00001289971,0.000001266545,0.000861718],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9978219,"threshold_uncertainty_score":0.04233426,"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."}}