{"id":"W4361024445","doi":"10.1161/blog.20131226.175800","title":"Who's at risk for stroke after TIA? The new Canadian TIA score","year":2013,"lang":"en","type":"dataset","venue":"","topic":"Cerebrovascular and Carotid Artery Diseases","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Institutes of Health; American Heart Association","keywords":"Stroke (engine); Internal medicine; Medicine; Stroke risk; Cardiology; Ischemic stroke; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008375579,0.001493695,0.001950468,0.00394901,0.0008230775,0.001551878,0.002804813,0.001435912,0.01031319],"category_scores_gemma":[0.008357474,0.0005157558,0.00198455,0.01001318,0.0003325339,0.0007493764,0.001099869,0.001555114,0.006210488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006756945,"about_ca_system_score_gemma":0.01267937,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8899603,"about_ca_topic_score_gemma":0.9201251,"domain_scores_codex":[0.9990568,0.00007284237,0.0001472353,0.0001992155,0.000331736,0.0001922731],"domain_scores_gemma":[0.9974937,0.0003577961,0.0004086386,0.0002196539,0.001183871,0.0003362283],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003415525,0.00003062682,0.03935392,0.000624948,0.000496129,0.00006746224,0.00003255982,0.0008942312,0.00003291034,0.000480897,0.9513702,0.006274577],"study_design_scores_gemma":[0.001516351,0.0000483353,0.4953217,0.001507344,0.001062783,0.0004541643,0.0002958644,0.004348502,0.0002634991,0.002187809,0.4927458,0.0002479257],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00178862,0.0004672578,0.00004105737,0.0001947524,0.00002280688,0.00001305913,0.9967341,0.00005321463,0.000685106],"genre_scores_gemma":[0.009213958,0.0007265009,0.0002296658,0.0001658046,0.00002307209,0.0001000326,0.9884061,0.00002757586,0.001107338],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1100397,"threshold_uncertainty_score":0.2213753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009499244729918034,"score_gpt":0.2246494508354371,"score_spread":0.215150206105519,"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."}}