{"id":"W4400314083","doi":"10.1016/j.jksus.2024.103337","title":"Correlation between platelet metrics and cardiovascular risk in prediabetes with coronary artery disease: A two-year cross-sectional study","year":2024,"lang":"en","type":"article","venue":"Journal of King Saud University - Science","topic":"Inflammatory Biomarkers in Disease Prognosis","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation","funders":"","keywords":"Medicine; Prediabetes; Internal medicine; Coronary artery disease; Waist; Cardiology; Diabetes mellitus; Body mass index; Glycated hemoglobin; Blood pressure; Type 2 diabetes; Endocrinology","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":[0.001908545,0.00009800086,0.0002102614,0.001001834,0.0002179282,0.0001164668,0.000140763,0.00002956067,0.000008621039],"category_scores_gemma":[0.0002327442,0.00008498559,0.0001088375,0.001317176,0.0004063864,0.0007920784,0.00008499584,0.0003206283,0.000001451422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003371919,"about_ca_system_score_gemma":0.0005509294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001627914,"about_ca_topic_score_gemma":0.00000317429,"domain_scores_codex":[0.9982832,0.00009044787,0.0002096182,0.0002658257,0.0009755526,0.000175374],"domain_scores_gemma":[0.9990837,0.0001749091,0.000119713,0.0001453106,0.0002406182,0.0002357623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003848436,0.00006750912,0.9942724,0.00004481578,0.0003422088,0.002512779,0.0002417814,0.0008199934,0.00001795771,0.00001576178,0.000007306144,0.00127262],"study_design_scores_gemma":[0.001686598,0.0002607739,0.9944644,0.0002022145,0.0004754282,0.0001345971,0.0005406025,0.002020759,0.00001277086,0.00003339727,0.00007943839,0.00008904737],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983299,0.0006715595,0.0004166049,0.00002035062,0.0001920079,0.0002349552,0.00001917833,0.00002055748,0.00009482921],"genre_scores_gemma":[0.999284,0.00004483103,0.0005513043,0.000004399161,0.00009124288,2.47621e-7,0.000001454515,0.000006608843,0.00001593651],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002378182,"threshold_uncertainty_score":0.3465612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.013930298829711,"score_gpt":0.2511767528066055,"score_spread":0.2372464539768945,"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."}}