{"id":"W2153608242","doi":"10.1001/archinternmed.2011.471","title":"Shared Electronic Vascular Risk Decision Support in Primary Care","year":2011,"lang":"en","type":"article","venue":"Archives of Internal Medicine","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Primary care; Primary (astronomy); Decision support system; Business; Medicine; Computer science; Family medicine; Data mining","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001194017,0.0002185038,0.0007049309,0.0004635981,0.00011562,8.980716e-7,0.0005501186,0.0001266134,0.0009997354],"category_scores_gemma":[0.0006121653,0.0001643206,0.0001138269,0.0002007961,0.000150864,0.00008465475,0.0001631404,0.00146448,0.0001040368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004087055,"about_ca_system_score_gemma":0.0009322071,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01228465,"about_ca_topic_score_gemma":0.003712699,"domain_scores_codex":[0.996049,0.0007730273,0.001436126,0.0003882452,0.000416311,0.0009372827],"domain_scores_gemma":[0.9971919,0.001363212,0.0005806687,0.0005431142,0.00009201132,0.0002290581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001473346,0.0001146063,0.7866488,0.001723075,0.0001135413,0.00004286677,0.07033099,0.000001268881,0.001141308,0.001331979,0.001299242,0.135779],"study_design_scores_gemma":[0.007416701,0.003911997,0.9416817,0.009991013,0.00007272635,0.00001883697,0.007477015,0.0001868613,0.0002340638,0.009658934,0.01904667,0.0003034699],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8194131,0.005083392,0.00648673,0.0001344168,0.001053819,0.001409738,0.00002020883,0.00006867143,0.16633],"genre_scores_gemma":[0.9953267,0.001560586,0.001504141,0.0005960574,0.0003310755,0.0001128201,0.00003528172,0.00004382241,0.0004895023],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1759137,"threshold_uncertainty_score":0.9999135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03096493475136522,"score_gpt":0.3706600606222769,"score_spread":0.3396951258709117,"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."}}