{"id":"W4391174376","doi":"10.4103/ijpvm.ijpvm_123_22","title":"Application of “Human Factor Analysis and Classification System” (HFACS) Model to the Prevention of Medical Errors and Adverse Events: A Systematic Review","year":2023,"lang":"en","type":"review","venue":"International Journal of Preventive Medicine","topic":"Patient Safety and Medication Errors","field":"Health Professions","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Isfahan University of Medical Sciences","keywords":"Causation; Scopus; Crew resource management; Medical literature; Adverse effect; MEDLINE; Medicine; Human error; Medical emergency; Risk analysis (engineering); Aviation; Pathology; Internal medicine; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03328257,0.002162295,0.01051421,0.01912623,0.001230007,0.003312777,0.002000767,0.002015502,0.003204068],"category_scores_gemma":[0.09791208,0.001149523,0.01337208,0.01594084,0.001484682,0.003707682,0.001474362,0.00135673,0.0002625193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007831028,"about_ca_system_score_gemma":0.02367797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01372372,"about_ca_topic_score_gemma":0.0262072,"domain_scores_codex":[0.958369,0.01817792,0.01162048,0.00241788,0.008840443,0.0005743209],"domain_scores_gemma":[0.9191802,0.06241553,0.009882921,0.001421382,0.0067248,0.0003752087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0002478313,0.00004143024,0.00413836,0.9112451,0.02248621,0.0001569043,0.0004159705,0.0003682874,0.0001240371,0.0006294619,0.00189751,0.05824899],"study_design_scores_gemma":[0.0006317637,0.0005939326,0.01409323,0.8103529,0.1563517,0.0004463648,0.0006432615,0.001055665,0.0003243418,0.001171605,0.01420299,0.0001323093],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00290473,0.9895196,0.001538957,0.0006463667,0.0003161957,0.004003875,0.00065827,0.00002900182,0.0003829592],"genre_scores_gemma":[0.05634638,0.9229999,0.009383663,0.0008819786,0.0002817906,0.009125724,0.0007099428,0.00001375791,0.0002568746],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.03328257,"threshold_uncertainty_score":0.1760171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1970931570510887,"score_gpt":0.5355952384633921,"score_spread":0.3385020814123034,"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."}}