{"id":"W2739875050","doi":"10.2196/medinform.7140","title":"Triaging Patient Complaints: Monte Carlo Cross-Validation of Six Machine Learning Classifiers","year":2017,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Medical Malpractice and Liability Issues","field":"Health Professions","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cross-validation; Monte Carlo method; Computer science; Artificial intelligence; Machine learning; Statistics; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06292277,0.002508449,0.002259253,0.003280859,0.001738784,0.001837961,0.002675532,0.003854805,0.001195407],"category_scores_gemma":[0.06920666,0.0008114108,0.002103418,0.001413181,0.001922588,0.001597544,0.001820161,0.003730557,0.0006441864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003014848,"about_ca_system_score_gemma":0.002769451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01647585,"about_ca_topic_score_gemma":0.01231797,"domain_scores_codex":[0.9785658,0.01501934,0.001817929,0.002298376,0.00147534,0.000823276],"domain_scores_gemma":[0.8671089,0.1067729,0.004026125,0.006994205,0.01371307,0.001384753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003655361,0.002680794,0.08006003,0.0002973104,0.001224645,0.0001620708,0.0004292529,0.8019032,0.001725174,0.001086464,0.003388161,0.1033876],"study_design_scores_gemma":[0.00009544178,0.0005047621,0.005022169,0.00004032843,0.00008044886,0.00003440823,0.00006429792,0.9921064,0.001330074,0.0004652905,0.0002305915,0.00002576391],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8840966,0.002190913,0.1072672,0.0005332165,0.0003535151,0.001554205,0.0007938733,0.001127372,0.002083144],"genre_scores_gemma":[0.9301767,0.0001739158,0.06645733,0.0002364689,0.00007387848,0.000512223,0.001672427,0.0000667411,0.0006304285],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06292277,"threshold_uncertainty_score":0.3327714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08262412564591218,"score_gpt":0.4701145027362492,"score_spread":0.387490377090337,"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."}}