{"id":"W2491576974","doi":"10.1161/circoutcomes.6.suppl_1.a340","title":"Abstract 340: Improved Patterns for Advanced Non-Invasive Diagnostic Testing Using a Personalized Gene Expression Score among Patients Presenting to Primary Care Clinicians with Symptoms of Suspected Obstructive Coronary Artery Disease: Results from the IMPACT-PCP (Investigation of a Molecular Personalized Coronary Gene Expression Test on Primary Care Practice Pattern) Trial","year":2013,"lang":"en","type":"article","venue":"Circulation Cardiovascular Quality and Outcomes","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"St.Amant","funders":"","keywords":"Medicine; Coronary artery disease; McNemar's test; Chest pain; Pre- and post-test probability; Internal medicine; Clinical endpoint; Logistic regression; Prospective cohort study; Ambulatory; Emergency medicine; Physical therapy; Clinical trial","routes":{"ca_aff":true,"ca_fund":false,"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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005153788,0.0005029145,0.00127209,0.0001351241,0.0002777548,0.000067619,0.0001449874,0.0001816586,0.000002815892],"category_scores_gemma":[0.009928741,0.000379878,0.0009301956,0.000230887,0.0002497944,0.0004453653,0.0001184596,0.0002771307,4.08664e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004397113,"about_ca_system_score_gemma":0.0004840429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001082299,"about_ca_topic_score_gemma":0.000004966606,"domain_scores_codex":[0.995936,0.0005534033,0.001135767,0.0008964082,0.001096379,0.000382057],"domain_scores_gemma":[0.9868457,0.008785304,0.001269673,0.000903569,0.001881295,0.0003144908],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006146683,0.0001938387,0.9171314,0.0009754364,0.001035898,0.00004081986,0.005694657,0.006995496,0.05912497,1.813221e-7,0.000001978672,0.002658667],"study_design_scores_gemma":[0.03574332,0.000394747,0.9469616,0.002548346,0.001692704,0.00001056883,0.003870561,0.0003810335,0.007974035,0.00001043205,3.974398e-7,0.0004122721],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9848772,0.001472978,0.004782159,0.00004138281,0.0001861886,0.006313183,0.00226716,0.00005069875,0.000009092826],"genre_scores_gemma":[0.990862,0.00002412918,0.004236034,0.0002349409,0.000178531,0.0002895051,0.004093152,0.00008079065,9.921076e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05115094,"threshold_uncertainty_score":0.9998653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03210750942935248,"score_gpt":0.2978862131940215,"score_spread":0.2657787037646691,"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."}}