{"id":"W4388268164","doi":"10.1016/j.jcjd.2023.10.375","title":"THE USE OF HSTNI AS AN INDEPENDENT RISK FACTOR IN A LARGE CANADIAN COHORT: NEW INSIGHTS IN CARDIOVASCULAR RISK ASSESSMENT","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Diabetes","topic":"Diverse Scientific Research Studies","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Medicine; Risk stratification; Cohort; Troponin I; Risk factor; Risk assessment; Framingham Risk Score; Cohort study; Risk analysis (engineering); Internal medicine; Computer science; Disease","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004870951,0.000178927,0.0005911369,0.001717099,0.001031843,0.0001099666,0.0006080221,0.0001602673,0.0002784606],"category_scores_gemma":[0.003720467,0.0001308395,0.0002144715,0.001274914,0.0001508653,0.0004880274,0.00008251904,0.001482071,0.0000824157],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001480603,"about_ca_system_score_gemma":0.01389414,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7529831,"about_ca_topic_score_gemma":0.9920805,"domain_scores_codex":[0.9947729,0.001903193,0.0008346929,0.0002742796,0.0008219703,0.001393029],"domain_scores_gemma":[0.9957135,0.0009494042,0.0004026897,0.0005418068,0.0004939593,0.001898641],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002407911,0.00001058349,0.9814008,0.00001936798,0.0003170127,0.0001169552,0.005077007,0.0004475667,0.00000363331,0.00009996491,0.009223115,0.003281511],"study_design_scores_gemma":[0.0008216142,0.00007520035,0.9052503,0.0001853042,0.00004229579,1.932425e-7,0.005845628,0.0002687824,0.000004893248,0.0005903903,0.08679968,0.0001157095],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951193,0.001271042,0.000001791722,0.000535177,0.001182782,0.000721603,0.0005898888,0.000006152006,0.0005722897],"genre_scores_gemma":[0.9983652,0.0006249044,0.00003731855,0.00009163909,0.0001103663,0.00002197818,0.000009932044,0.00002216615,0.0007164974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2390974,"threshold_uncertainty_score":0.9916962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08267918667403808,"score_gpt":0.3699138418521938,"score_spread":0.2872346551781558,"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."}}