{"id":"W2529203253","doi":"10.1007/s13721-016-0137-2","title":"A new approach to distinguish migraine from stroke by mining structured and unstructured clinical data-sources","year":2016,"lang":"en","type":"article","venue":"Network Modeling Analysis in Health Informatics and Bioinformatics","topic":"Neurological Disorders and Treatments","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Island Health; University of Victoria","funders":"","keywords":"Migraine; Triage; Computer science; Stroke (engine); Machine learning; Artificial intelligence; Data mining; Class (philosophy); Medicine; Data science; Medical emergency; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002004588,0.0009490711,0.0007964839,0.004990801,0.0008159182,0.002035586,0.001205522,0.0008987623,0.0009105522],"category_scores_gemma":[0.006030806,0.0003304071,0.001679932,0.003070745,0.0004503454,0.002193497,0.00168072,0.001350112,0.0005154732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006077862,"about_ca_system_score_gemma":0.001722408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006235773,"about_ca_topic_score_gemma":0.0105905,"domain_scores_codex":[0.998551,0.0003172395,0.0001901237,0.0005032195,0.0003710915,0.0000674149],"domain_scores_gemma":[0.9963661,0.002068793,0.0003274138,0.0004980247,0.0005864463,0.0001531832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008830035,0.001191776,0.08239087,0.0008687237,0.001668012,0.001222285,0.001213675,0.09930929,0.01868493,0.04555954,0.02742536,0.7195826],"study_design_scores_gemma":[0.00003213658,0.00006350156,0.005317666,0.00006707537,0.0002059555,0.0004238837,0.0002419165,0.9374191,0.002709896,0.04614399,0.00734132,0.00003346716],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02390687,0.0006040867,0.9660007,0.001396727,0.0001064564,0.0002466427,0.004817818,0.001786345,0.001134342],"genre_scores_gemma":[0.2217059,0.0005562379,0.7647919,0.0003848104,0.0001839563,0.0002793292,0.01039829,0.0001209673,0.001578592],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006235773,"threshold_uncertainty_score":0.01239896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08413513986309411,"score_gpt":0.3294236188600709,"score_spread":0.2452884789969768,"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."}}