{"id":"W4386532238","doi":"10.1130/ges02661.1","title":"Geoscience academic hiring networks reinforce historic patterns of inequity","year":2023,"lang":"en","type":"article","venue":"Geosphere","topic":"Radiology practices and education","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Institution; Workforce; Disadvantage; Indigenous; Work (physics); Social network analysis; Underrepresented Minority; Quarter (Canadian coin); Political science; Sociology; Geography; Social science; Medicine; Medical education; Engineering; Law; Ecology; Archaeology","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":[0.001697476,0.00009065687,0.0001636495,0.002669321,0.001004417,0.00135611,0.0004979268,0.0003415686,0.003676441],"category_scores_gemma":[0.01098105,0.0001499357,0.0001157088,0.003275696,0.0008792128,0.0020274,0.00162368,0.0003890872,0.00022407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001113205,"about_ca_system_score_gemma":0.0005214079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01522723,"about_ca_topic_score_gemma":0.03075967,"domain_scores_codex":[0.9987608,0.0004545513,0.00008742572,0.0002820963,0.0002052252,0.0002098672],"domain_scores_gemma":[0.9920849,0.002891114,0.002799817,0.0006869405,0.0008845652,0.0006527136],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007666257,0.00004786348,0.9597667,0.0000731952,0.00006273364,0.00009236536,0.01082146,0.0005074936,0.0004922355,0.005101678,0.001364004,0.02159352],"study_design_scores_gemma":[0.000003741228,0.00003461821,0.9728458,0.00009146659,0.00002125027,0.0001101855,0.01625398,0.001632253,0.0002267218,0.002938046,0.005829791,0.00001220573],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928058,0.0003117622,0.00105513,0.0007409533,0.00001326925,0.00001194803,0.0005488796,0.00001190903,0.004500414],"genre_scores_gemma":[0.999307,0.00007337089,0.0002240164,0.00003244057,0.000008540707,0.000005728013,0.0001709589,0.000002637414,0.0001752058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9983025,"threshold_uncertainty_score":0.03027719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0382176777699486,"score_gpt":0.3260942838392361,"score_spread":0.2878766060692875,"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."}}