{"id":"W2099744219","doi":"10.1161/strokeaha.110.588335","title":"Gene Expression Profiling of Blood for the Prediction of Ischemic Stroke","year":2010,"lang":"en","type":"article","venue":"Stroke","topic":"Cerebrovascular and genetic disorders","field":"Medicine","cited_by":149,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke; U.S. Public Health Service; University of Cincinnati; Canadian Institutes of Health Research; MIND Institute, University of California, Davis","keywords":"Medicine; Ischemic stroke; Stroke (engine); Gene expression profiling; Profiling (computer programming); Internal medicine; Gene; Gene expression; Cardiology; Ischemia; Genetics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0005336161,0.0002797646,0.0003094342,0.0006865446,0.0001273603,0.0003179156,0.0001732413,0.0002798252,0.0007873519],"category_scores_gemma":[0.0008998476,0.0000832576,0.0001314301,0.000428756,0.000206881,0.0001264965,0.0001194021,0.0003224737,0.0003405614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002098219,"about_ca_system_score_gemma":0.0002248589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003839085,"about_ca_topic_score_gemma":0.0005953267,"domain_scores_codex":[0.9997377,0.00009397909,0.00001368965,0.00006948782,0.00005885926,0.00002620624],"domain_scores_gemma":[0.9996846,0.0001525385,0.0000624747,0.00001900214,0.00004606526,0.00003532923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.003110817,0.0005947985,0.4078602,0.0002461827,0.0001970835,0.0002482153,0.0001376866,0.001265763,0.5075659,0.0002200883,0.001292697,0.07726061],"study_design_scores_gemma":[0.0001164029,0.002223271,0.858459,0.00006208696,0.0002822436,0.0009695656,0.0001403524,0.01024024,0.1235029,0.0009093827,0.003054504,0.00004012288],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861034,0.003149561,0.007919237,0.0002968839,0.00005904323,0.00008510401,0.001182266,0.00008854795,0.001115931],"genre_scores_gemma":[0.9893601,0.0009355524,0.0080883,0.0001400326,0.00005011231,0.00009559183,0.0008614361,0.00000878762,0.000460126],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007873519,"threshold_uncertainty_score":0.002822042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01013231810759898,"score_gpt":0.2442789527821874,"score_spread":0.2341466346745884,"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."}}