{"id":"W3173478665","doi":"","title":"Cardio Vascular Ailments Prediction and Analysis Based On Deep Learning Techniques","year":2021,"lang":"en","type":"article","venue":"","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trinity College","funders":"","keywords":"Computer science; Artificial intelligence; Random forest; Machine learning; Measure (data warehouse); Classifier (UML); Data mining","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007938463,0.0001142699,0.0002661455,0.0002074849,0.0007818314,0.00001265723,0.00005702116,0.0002126958,0.001069944],"category_scores_gemma":[0.0003779719,0.0001045725,0.0001235042,0.0006587891,0.00002930274,0.00006909025,0.00005752584,0.0005823246,0.00008581346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001688147,"about_ca_system_score_gemma":0.0001268125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000815898,"about_ca_topic_score_gemma":0.0007266553,"domain_scores_codex":[0.9976206,0.0009824088,0.0004128007,0.0003649216,0.0003039662,0.0003152536],"domain_scores_gemma":[0.9987205,0.000408098,0.00008930235,0.0003276104,0.0003211424,0.0001333788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001625179,0.00002979271,0.9762648,0.00009613382,0.0001604027,0.00001065912,0.0007371781,0.002122971,0.0002531141,0.0003409262,0.0001396821,0.01982806],"study_design_scores_gemma":[0.0002792192,0.0003633175,0.2071599,0.0004143786,0.0009572232,0.000001115684,0.01451396,0.7116845,0.01724593,0.0006721937,0.04622572,0.0004825977],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6386545,0.0006428718,0.3049805,0.002485521,0.0007509877,0.001758895,0.00002530919,0.001323789,0.04937764],"genre_scores_gemma":[0.9913812,0.0001994604,0.005395779,0.00133154,0.0001471888,0.0001638908,0.00009071733,0.00002082786,0.001269366],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.769105,"threshold_uncertainty_score":0.9998432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07552928889282962,"score_gpt":0.4390196602435789,"score_spread":0.3634903713507492,"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."}}