{"id":"W2152030904","doi":"10.1016/eupace/4.supplement_2.b157-a","title":"P-386 Sex bias in pacemaker selection","year":2003,"lang":"en","type":"article","venue":"EP Europace","topic":"Cardiac pacing and defibrillation studies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hôpital Fleurimont","funders":"","keywords":"Medicine; Selection (genetic algorithm); Selection bias; Internal medicine; Cardiology; Artificial intelligence; Pathology","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":[],"consensus_categories":[],"category_scores_codex":[0.0002364163,0.00008534166,0.0002145656,0.00009493311,0.00004481156,0.00001058223,0.000003009249,0.00003163139,0.00003318103],"category_scores_gemma":[0.0004593862,0.00007594831,0.00005885099,0.0003701012,0.00002045504,0.00002732474,0.000008227578,0.0001025792,0.0002172947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004172619,"about_ca_system_score_gemma":0.00003119112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000192575,"about_ca_topic_score_gemma":0.00000903883,"domain_scores_codex":[0.9993127,0.0001018238,0.0001231056,0.0001641183,0.0001463935,0.0001518506],"domain_scores_gemma":[0.9996844,0.000070491,0.00003158279,0.0001150227,0.00004864859,0.00004984094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000889225,0.00007626918,0.9205247,0.00006300806,0.00007898897,0.0001005861,0.001989016,0.0002860217,0.004494821,0.0008682506,0.07021791,0.001211546],"study_design_scores_gemma":[0.001219069,0.0001121297,0.2077664,0.00004914098,0.00003669385,0.001070609,0.0005272411,0.00006205729,0.004158217,0.00004474505,0.7847944,0.0001592843],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5986909,0.0005611941,0.0002610697,0.000224705,0.0001449547,0.0001027926,7.02996e-7,0.00007453877,0.3999391],"genre_scores_gemma":[0.9765262,0.00008721049,0.0002470871,0.000251265,0.00008589906,0.000003056074,0.000001310911,0.00001546027,0.02278253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7145765,"threshold_uncertainty_score":0.3097082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05485391970568154,"score_gpt":0.3122393062294875,"score_spread":0.2573853865238059,"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."}}