{"id":"W2100435000","doi":"10.1016/j.yebeh.2009.11.017","title":"A common strategy and database to compare the performance of seizure prediction algorithms","year":2009,"lang":"en","type":"article","venue":"Epilepsy & Behavior","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Milestone; Epilepsy; Set (abstract data type); Computer science; Competition (biology); Epileptic seizure; Data set; Algorithm; Artificial intelligence; Machine learning; Data mining; Psychology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006841464,0.001463855,0.00186,0.005036353,0.001077351,0.0033192,0.002825833,0.002261942,0.005366825],"category_scores_gemma":[0.02750924,0.0003764736,0.001650821,0.004396561,0.0007376232,0.002145478,0.002232723,0.001481409,0.003334936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008026857,"about_ca_system_score_gemma":0.001317144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003638639,"about_ca_topic_score_gemma":0.003114706,"domain_scores_codex":[0.9908698,0.002112703,0.002693816,0.001070598,0.002791549,0.0004614883],"domain_scores_gemma":[0.9792823,0.00489588,0.001263206,0.006430909,0.007551528,0.0005762489],"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":[0.008484075,0.007815911,0.06209282,0.002455129,0.00319669,0.0006065612,0.0006472864,0.04249058,0.06061881,0.01996222,0.08351083,0.7081192],"study_design_scores_gemma":[0.004049986,0.03014957,0.2025789,0.001019065,0.00266014,0.005297395,0.002757484,0.2279145,0.2614537,0.03567901,0.224991,0.00144921],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5152432,0.004806915,0.3243918,0.00178901,0.003029322,0.008788276,0.09840743,0.01248341,0.03106068],"genre_scores_gemma":[0.6704983,0.001739307,0.1849003,0.001497637,0.000418862,0.01208112,0.1154205,0.001388778,0.01205527],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.006841464,"threshold_uncertainty_score":0.03618157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04027278248288022,"score_gpt":0.3048510519164048,"score_spread":0.2645782694335246,"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."}}