{"id":"W4315647676","doi":"10.24041/ejmr2022.28","title":"BIBLIOMETRIC ANALYSIS OF EMERGENCY MEDICINE","year":2022,"lang":"en","type":"article","venue":"Era s journal of medical research","topic":"Emergency Medicine Education and Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Specialty; Medicine; Scope (computer science); Medical education; Emergency medicine; Family medicine; Computer science","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01168592,0.0009655539,0.003272,0.1515763,0.001434203,0.005134243,0.001298818,0.0008623255,0.008493182],"category_scores_gemma":[0.08989235,0.0003376389,0.003983288,0.1860319,0.0009200554,0.002863484,0.002202499,0.0005131123,0.001576647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003567633,"about_ca_system_score_gemma":0.005487929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004399317,"about_ca_topic_score_gemma":0.003559651,"domain_scores_codex":[0.9645045,0.009593181,0.006027046,0.002352321,0.01672134,0.0008015976],"domain_scores_gemma":[0.9343095,0.04380839,0.009024742,0.002478839,0.00974416,0.0006343483],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005606786,0.0002787564,0.3619171,0.05216693,0.009961898,0.001374282,0.004154157,0.009136667,0.001932294,0.01980558,0.03343045,0.5052812],"study_design_scores_gemma":[0.0001536987,0.0004873511,0.750286,0.008080311,0.007482209,0.003671825,0.008737195,0.02320751,0.003223773,0.02645537,0.1679029,0.0003118762],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5442737,0.163934,0.03998011,0.00561608,0.00152688,0.004185007,0.1072615,0.00183782,0.1313849],"genre_scores_gemma":[0.918014,0.03473195,0.01694122,0.0002592113,0.0007430805,0.002328594,0.02262239,0.0001443231,0.004215333],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8484237,"threshold_uncertainty_score":0.06180179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2784119631659733,"score_gpt":0.5806706281882041,"score_spread":0.3022586650222308,"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."}}