{"id":"W2979658440","doi":"","title":"응급의료기관 평가에서 한국 응급환자 중증도 분류기준의 오용","year":2019,"lang":"ko","type":"article","venue":"대한응급의학회지","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Triage; Reimbursement; Medical emergency; Scale (ratio); Medicine; Political science; Geography; Health care; Cartography","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":[0.001533442,0.0002068062,0.0003026841,0.001281379,0.0005712117,0.0008604435,0.000400781,0.0002001105,0.0165317],"category_scores_gemma":[0.007302941,0.00008911559,0.0003918115,0.001270922,0.0003782135,0.0007023221,0.0008177781,0.0005121676,0.005094639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008595998,"about_ca_system_score_gemma":0.002630939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007924533,"about_ca_topic_score_gemma":0.009768495,"domain_scores_codex":[0.9983662,0.0003262402,0.0003185744,0.0001936655,0.000619664,0.0001755676],"domain_scores_gemma":[0.9962718,0.0003315728,0.0008639326,0.0001569907,0.002005105,0.0003706314],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005603537,0.0003656367,0.4299479,0.0009067234,0.0002781145,0.0005544688,0.001358028,0.0003221194,0.002377035,0.009001131,0.1069736,0.447355],"study_design_scores_gemma":[0.0001069772,0.0003878576,0.7765045,0.0006220847,0.0001898849,0.002512581,0.002228613,0.0006850467,0.00173154,0.004965771,0.2099687,0.00009643241],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5910802,0.01018344,0.02477069,0.01831397,0.00198833,0.002349807,0.03059056,0.0006527712,0.3200703],"genre_scores_gemma":[0.9171066,0.006330059,0.01225227,0.003149762,0.0005268726,0.001113136,0.01551904,0.00009015638,0.04391224],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9984666,"threshold_uncertainty_score":0.05530405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0127410571351999,"score_gpt":0.2810058835994612,"score_spread":0.2682648264642613,"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."}}