{"id":"W3204863995","doi":"10.3390/biomedicines9101357","title":"Treatment Efficacy Analysis in Acute Ischemic Stroke Patients Using In Silico Modeling Based on Machine Learning: A Proof-of-Principle","year":2021,"lang":"en","type":"article","venue":"Biomedicines","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Children's Hospital; Hotchkiss Brain Institute; University of Calgary","funders":"Canada Research Chairs; Heart and Stroke Foundation of Canada","keywords":"Proof of concept; In silico; Stroke (engine); Ischemic stroke; Machine learning; Medicine; Computer science; Artificial intelligence; Cardiology; Ischemia; Engineering; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001574811,0.000281441,0.0007908886,0.00125314,0.00002836043,0.000007018894,0.00009804549,0.0001016244,0.00005916738],"category_scores_gemma":[0.0002144584,0.000226254,0.0002006084,0.001907613,0.00005198871,0.00003897598,0.00007779188,0.000193221,0.00000215111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003577193,"about_ca_system_score_gemma":0.0001447076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002678495,"about_ca_topic_score_gemma":0.00004754161,"domain_scores_codex":[0.9979607,0.00006495856,0.0006299463,0.0005152344,0.0004908692,0.0003382207],"domain_scores_gemma":[0.9990647,0.00008863908,0.0001626374,0.0004559693,0.0001148176,0.0001131925],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005604513,0.001957964,0.9271059,0.0001131738,0.0008292347,0.0002802296,0.0003226385,0.04156172,0.02366023,0.000001520417,0.00003286119,0.003574102],"study_design_scores_gemma":[0.01005487,0.000704427,0.02774908,0.0003197325,0.001562136,0.000004117596,0.000159239,0.9329783,0.0251162,3.437767e-7,0.00116484,0.0001867101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961863,0.0003468267,0.001443782,0.0004325566,0.00007110335,0.0005406332,0.00002405763,0.00003011048,0.0009246641],"genre_scores_gemma":[0.9965436,0.00003908263,0.002192845,0.000126729,0.00005357231,0.00002873106,0.0004840824,0.00002916585,0.0005021863],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8993568,"threshold_uncertainty_score":0.9226369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02674287925347144,"score_gpt":0.3057375639440582,"score_spread":0.2789946846905867,"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."}}