{"id":"W4399282172","doi":"10.3390/neurolint16030045","title":"Introducing the Futile Recanalization Prediction Score (FRPS): A Novel Approach to Predict and Mitigate Ineffective Recanalization after Endovascular Treatment of Acute Ischemic Stroke","year":2024,"lang":"en","type":"article","venue":"Neurology International","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Education, Culture, Sports, Science and Technology; Japan Society for the Promotion of Science; Canadian Institutes of Health Research; Australian Academy of Science; Government of Canada","keywords":"Medicine; Generalizability theory; Random forest; Stroke (engine); Atrial fibrillation; Internal medicine; Predictive modelling; Cardiology; Machine learning; Statistics; Computer science","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":[0.01016882,0.001859507,0.001801772,0.004030812,0.0003067384,0.001557151,0.0009863738,0.0009648615,0.001490996],"category_scores_gemma":[0.02639031,0.0003413365,0.0028016,0.001797938,0.000478687,0.00121698,0.001017217,0.001297921,0.0003105143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005749429,"about_ca_system_score_gemma":0.001520485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002103809,"about_ca_topic_score_gemma":0.003578979,"domain_scores_codex":[0.9953495,0.002367134,0.0004384313,0.0006101578,0.001104177,0.0001306072],"domain_scores_gemma":[0.9840236,0.01017366,0.003458786,0.0005499528,0.001529029,0.0002650526],"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":[0.002757367,0.0004732628,0.5583184,0.002249807,0.008190977,0.000232536,0.0002132213,0.04932542,0.001449327,0.002530612,0.005618307,0.3686407],"study_design_scores_gemma":[0.001010378,0.006142243,0.3596646,0.001896285,0.01504328,0.001688144,0.0003113442,0.5782531,0.005295947,0.01661502,0.01358696,0.0004925699],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6235428,0.03339301,0.3196578,0.004383093,0.0008256208,0.001001932,0.007434132,0.001522433,0.00823919],"genre_scores_gemma":[0.9386964,0.002555605,0.05518629,0.0004039187,0.0004578561,0.0003892436,0.001651242,0.0000468685,0.0006125898],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01016882,"threshold_uncertainty_score":0.05377853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00897184503260794,"score_gpt":0.2367414787019581,"score_spread":0.2277696336693501,"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."}}