{"id":"W4411713439","doi":"10.55041/ijsrem51058","title":"CardioNet.AI - Heart Disease Predictor Model","year":2025,"lang":"en","type":"article","venue":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Cardiology; Disease; Internal medicine; Medicine; Artificial intelligence; Computer science","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":[0.005376714,0.00008859231,0.000184873,0.001512844,0.0003872525,0.00007281203,0.0002708115,0.00005082141,0.00002245508],"category_scores_gemma":[0.0002823434,0.00007849232,0.00006457376,0.0006728795,0.0001423701,0.0002129645,0.0002359819,0.000886222,0.00001794976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002759162,"about_ca_system_score_gemma":0.0002707846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003271346,"about_ca_topic_score_gemma":0.00001419002,"domain_scores_codex":[0.9976125,0.0002445313,0.0006968511,0.0002317259,0.0007620283,0.0004524107],"domain_scores_gemma":[0.9985135,0.000385439,0.00005759662,0.0001976355,0.0006417735,0.0002040756],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001037083,0.0004330996,0.08788839,0.008492922,0.0002501445,0.0003786409,0.002630813,0.4279096,0.001534236,0.311898,0.1468096,0.01073751],"study_design_scores_gemma":[0.0007525687,0.00008175413,0.04101929,0.01018648,0.00002743819,0.000005865841,0.001948851,0.8213624,0.00005833558,0.04895487,0.07539807,0.0002040724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9005116,0.002714621,0.05147034,0.0339787,0.007170083,0.001628269,0.00004138341,0.00005172463,0.00243326],"genre_scores_gemma":[0.9959002,0.0001964883,0.0009632775,0.0001856546,0.0001193018,0.00005372755,0.00000273108,0.000008379853,0.002570214],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3934529,"threshold_uncertainty_score":0.3850243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1558939377960435,"score_gpt":0.5085537581160609,"score_spread":0.3526598203200173,"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."}}