{"id":"W2316093659","doi":"10.7748/ns.29.12.33.s40","title":"Stroke Risk Calculator app","year":2014,"lang":"en","type":"article","venue":"Nursing Standard","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services","funders":"","keywords":"Calculator; Stroke (engine); Medicine; Stroke risk; Medical emergency; Ischemic stroke; Computer science; Engineering; Psychiatry","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":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001375658,0.000170537,0.0003186117,0.00009370483,0.001596409,0.00001546029,0.00019724,0.000285204,0.0006853039],"category_scores_gemma":[0.001140598,0.0001566985,0.00008378574,0.000165158,0.0001703552,0.00009009679,0.00002873658,0.0009943689,0.000945153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006760782,"about_ca_system_score_gemma":0.0003058492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007000777,"about_ca_topic_score_gemma":0.0004829169,"domain_scores_codex":[0.9969872,0.0008401994,0.0005882211,0.0003558948,0.0004649066,0.0007635487],"domain_scores_gemma":[0.9979236,0.0006970848,0.0002515792,0.0005180943,0.0003401072,0.0002695007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004743911,0.0000671658,0.3274531,0.000153616,0.00002766159,0.000003896615,0.01666471,0.000121944,0.0003554271,0.04250859,0.05198493,0.5601846],"study_design_scores_gemma":[0.001041549,0.0009069665,0.02744406,0.002611291,0.0001281945,0.000004059539,0.01890065,0.01491724,0.003339496,0.05998443,0.8698054,0.0009166478],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8538433,0.0003134132,0.06347574,0.004188719,0.006342665,0.001105046,0.0003404331,0.0007261325,0.06966449],"genre_scores_gemma":[0.9942628,0.00002383313,0.002195393,0.0006078401,0.001110924,0.00004039989,0.000009342556,0.00004941106,0.00170007],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8178205,"threshold_uncertainty_score":0.9998327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0669366383227845,"score_gpt":0.4716580574960077,"score_spread":0.4047214191732232,"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."}}