{"id":"W3043370368","doi":"10.1136/bmj.b2899","title":"Clinical prediction rules","year":2009,"lang":"en","type":"article","venue":"BMJ","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Clinical prediction rule; Set (abstract data type); Computer science; Medicine; Operations research; Data mining; Artificial intelligence; Mathematics; Pathology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001439662,0.00005527862,0.0001491679,0.00003007736,0.00002746664,0.000008753795,0.00003254083,0.00007354604,0.0002845209],"category_scores_gemma":[0.004904574,0.00004717476,0.00008952032,0.00006063042,0.00002232446,0.0001026314,0.0000103733,0.0001741104,0.0003909238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002228704,"about_ca_system_score_gemma":0.0000807078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009866442,"about_ca_topic_score_gemma":0.000002773154,"domain_scores_codex":[0.998547,0.0000704085,0.0009150592,0.0001584924,0.0002050703,0.000103957],"domain_scores_gemma":[0.9990667,0.0003561937,0.0001510285,0.0002272249,0.00009841561,0.0001004535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003504826,0.0003199889,0.1056347,0.000006134843,0.0000295246,0.00002614022,0.00002022427,0.000002175828,0.0003266854,0.000434061,0.3569625,0.5358874],"study_design_scores_gemma":[0.001646285,0.0007427777,0.8577802,0.00002548534,0.0001029123,0.00006050353,0.00005142394,0.0007527098,0.00003646541,0.001104626,0.1376477,0.00004891282],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8430154,0.00006427496,0.003994514,0.1251028,0.0009771278,0.0008591717,0.00001529245,0.0002283874,0.02574302],"genre_scores_gemma":[0.9628735,0.00007383029,0.01874753,0.01433808,0.002904125,0.000007114996,0.0001159424,0.000008321635,0.0009315917],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7521455,"threshold_uncertainty_score":0.5871587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3418623717227494,"score_gpt":0.5814080069484786,"score_spread":0.2395456352257292,"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."}}