{"id":"W3216277561","doi":"10.1161/circ.144.suppl_1.14107","title":"Abstract 14107: Racial and Income Inequities in Cardiovascular Disease in Cancer versus Non-Cancer Patients: Propensity Score and Machine Learning Augmented Nationally Representative Case-Control Study of Mortality and Cost Among 30 Million Hospitalizations","year":2021,"lang":"en","type":"article","venue":"Circulation","topic":"Cardiovascular Health and Risk Factors","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Heart Institute","funders":"","keywords":"Medicine; Propensity score matching; Cancer; Disease; Disease control; Gerontology; Environmental health; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002755585,0.0002979602,0.0004078413,0.0008299316,0.0005168321,0.0008444336,0.0007856461,0.0004186913,0.002474021],"category_scores_gemma":[0.0073826,0.0002814705,0.0008443949,0.001745329,0.0003045828,0.0005148331,0.000750752,0.0007123829,0.0003274669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004339923,"about_ca_system_score_gemma":0.0006454905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006137528,"about_ca_topic_score_gemma":0.005771591,"domain_scores_codex":[0.9981874,0.0007603928,0.00022255,0.0004182625,0.0003072464,0.0001042615],"domain_scores_gemma":[0.9960285,0.0006910405,0.00174003,0.0008267455,0.0004459464,0.0002676693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002229989,0.0000771202,0.9948301,0.00002412552,0.0004070249,0.00003375261,0.00004887871,0.0003350025,0.0001250578,0.0001362648,0.001383092,0.00237656],"study_design_scores_gemma":[0.00006341322,0.0001629696,0.9939625,0.00002023382,0.0002684617,0.000176689,0.000105717,0.003379012,0.0001873429,0.0002868997,0.001374327,0.00001248659],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902519,0.0002320332,0.002448074,0.0003542403,0.00004391463,0.00007703076,0.005973947,0.000035317,0.0005834659],"genre_scores_gemma":[0.9928296,0.00008143631,0.001215987,0.0001121154,0.0000476432,0.00008372605,0.00524586,0.000009653933,0.0003740421],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006137528,"threshold_uncertainty_score":0.0145731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04792478398247325,"score_gpt":0.3192047334598202,"score_spread":0.271279949477347,"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."}}