{"id":"W2210225355","doi":"10.36834/cmej.36653","title":"Internal Medicine residents use heuristics to estimate disease probability","year":2015,"lang":"en","type":"article","venue":"Canadian Medical Education Journal","topic":"Clinical Reasoning and Diagnostic Skills","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Heuristics; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.01331987,0.000425718,0.0003374434,0.000853556,0.0003138997,0.001500921,0.0007304522,0.0009252689,0.00239551],"category_scores_gemma":[0.09055665,0.0003549221,0.0005073942,0.0003971024,0.001143334,0.001125974,0.001242963,0.0011191,0.0003506255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007706478,"about_ca_system_score_gemma":0.001340795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001234192,"about_ca_topic_score_gemma":0.001475605,"domain_scores_codex":[0.9923774,0.00482805,0.0005066789,0.0006455709,0.001364499,0.0002777633],"domain_scores_gemma":[0.9158613,0.06413598,0.01279093,0.003611899,0.002306432,0.001293516],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001876804,0.001482911,0.695314,0.001041615,0.0007205666,0.000360792,0.00673249,0.01065782,0.009015596,0.003130552,0.003100685,0.2665662],"study_design_scores_gemma":[0.0007594234,0.006511751,0.8667344,0.001710209,0.0008907088,0.002226481,0.006582012,0.05397461,0.0154566,0.03069772,0.01412939,0.0003266121],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9744312,0.0004861505,0.02026128,0.001008658,0.00002964939,0.0001550119,0.0000479172,0.000131333,0.0034489],"genre_scores_gemma":[0.9854253,0.0003367598,0.01350175,0.0003839881,0.00002242071,0.00006361988,0.00005161759,0.000008855506,0.0002058294],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01331987,"threshold_uncertainty_score":0.07044303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05124538891326132,"score_gpt":0.4136426834532611,"score_spread":0.3623972945399997,"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."}}