{"id":"W2097302145","doi":"10.4338/aci-2013-04-ra-0029","title":"Comparing predictions made by a prediction model, clinical score, and physicians","year":2013,"lang":"en","type":"article","venue":"Applied Clinical Informatics","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Children's Hospital of Eastern Ontario; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; University of Ottawa","keywords":"McNemar's test; Predictive modelling; Receiver operating characteristic; Naive Bayes classifier; Machine learning; Artificial intelligence; Emergency department; Computer science; Medicine; Data mining; Statistics; Support vector machine; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001169804,0.0002053786,0.0004663346,0.00006277263,0.000258812,0.0002589039,0.0006762167,0.0002735364,0.00000837439],"category_scores_gemma":[0.0002112291,0.0001924841,0.0001042092,0.0002438674,0.0002337288,0.0007876199,0.0005054415,0.001154995,0.00018667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003144968,"about_ca_system_score_gemma":0.00007889733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003929053,"about_ca_topic_score_gemma":0.000003595728,"domain_scores_codex":[0.9967648,0.0001006933,0.002041144,0.0003122489,0.0003728611,0.0004081994],"domain_scores_gemma":[0.9975556,0.0007486272,0.000512894,0.0007453732,0.0001119754,0.0003255155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003194357,0.0007696106,0.3986939,0.0003837528,0.0001971287,8.46272e-7,0.004086317,0.03260902,0.00001939973,0.09419081,0.1500408,0.3189764],"study_design_scores_gemma":[0.0005782868,0.0001429227,0.03666551,0.00003363159,0.00001604816,0.000003533699,0.0001047123,0.9568328,0.000002730317,0.003655027,0.001798804,0.000165933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2297641,0.00002319039,0.7588152,0.0009102981,0.0004406818,0.0006619312,0.00001245589,0.0005328636,0.008839183],"genre_scores_gemma":[0.9096028,0.0001474392,0.08639769,0.003367744,0.000204825,0.0001081112,0.00003506715,0.00001668962,0.0001195961],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9242238,"threshold_uncertainty_score":0.7849273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06969168858235335,"score_gpt":0.3510963986171176,"score_spread":0.2814047100347642,"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."}}