{"id":"W4220695610","doi":"10.1101/2022.03.29.22273128","title":"Faster, higher, stronger – together? A bibliometric analysis of author distribution in top medical education journals","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Innovations in Medical Education","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Wilson Centre; Women's College Hospital; University of Toronto; University Health Network","funders":"","keywords":"Publishing; Dominance (genetics); Equity (law); Political science; Bibliometrics; Library science; Social science; Sociology; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01716198,0.0007536429,0.002567016,0.1325269,0.001705228,0.009950656,0.001250303,0.0008514743,0.004942976],"category_scores_gemma":[0.1333528,0.0004109063,0.002476863,0.2171011,0.001550718,0.007392761,0.003481958,0.0007271608,0.001362833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001889161,"about_ca_system_score_gemma":0.00290204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003020005,"about_ca_topic_score_gemma":0.003210944,"domain_scores_codex":[0.9685937,0.007105127,0.008719279,0.002740105,0.01158971,0.001252153],"domain_scores_gemma":[0.778339,0.1400625,0.04942879,0.006781597,0.02266433,0.002723685],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004990277,0.0001153102,0.8656138,0.01172712,0.004130451,0.0005651049,0.005876696,0.001132058,0.001141154,0.003518537,0.007918861,0.09776185],"study_design_scores_gemma":[0.00008901418,0.0002231776,0.9390375,0.00302183,0.002451869,0.00172819,0.01223536,0.003420256,0.001117513,0.007211961,0.02932266,0.0001407328],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.89209,0.04539957,0.003495044,0.00402297,0.0003270404,0.0005834333,0.03596751,0.0003431306,0.01777129],"genre_scores_gemma":[0.9726241,0.01239959,0.004301976,0.0001856251,0.0003977755,0.0003863074,0.008663001,0.00008736006,0.0009542697],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.982838,"threshold_uncertainty_score":0.09076232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04730730957842356,"score_gpt":0.4126224041877682,"score_spread":0.3653150946093447,"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."}}