{"id":"W3209398659","doi":"10.82308/46880","title":"Adaptive control of epileptic seizures using reinforcement learning","year":2010,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reinforcement; Epilepsy; Psychology; Reinforcement learning; Control (management); Cognitive psychology; Neuroscience; Computer science; Artificial intelligence; Social psychology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000759895,0.0004031672,0.0004965572,0.0002471328,0.0007989717,0.0000739237,0.0007047875,0.0002226166,0.0002370118],"category_scores_gemma":[0.001504805,0.0003797759,0.0002274739,0.0003895239,0.0002568743,0.0007414941,0.000281075,0.001435525,0.0001064996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001185094,"about_ca_system_score_gemma":0.00003311544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001203471,"about_ca_topic_score_gemma":0.00003940562,"domain_scores_codex":[0.9967866,0.000413261,0.0007089938,0.000764669,0.0006559562,0.0006705547],"domain_scores_gemma":[0.9978111,0.0007681735,0.0004905857,0.0005170922,0.0001856877,0.0002273099],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000112332,0.00008039644,0.00007892522,0.00003040628,0.00003166848,0.00004501712,0.00001274831,0.009185467,0.9304407,0.04617714,9.326324e-7,0.01380423],"study_design_scores_gemma":[0.001282515,0.0004725691,0.000135414,0.0001157306,0.00005469252,0.0001298812,0.00006829442,0.02643169,0.9586956,0.002911076,0.009205618,0.0004969242],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9818915,0.00001936734,0.0001047692,0.00001925799,0.000842508,0.0004213879,0.00007556245,0.000189979,0.0164357],"genre_scores_gemma":[0.9974323,0.000007423067,0.0012154,0.0006983306,0.0000567792,0.00001763696,0.000002032634,0.00006285606,0.0005072671],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04326606,"threshold_uncertainty_score":0.9998654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02939945097830273,"score_gpt":0.2553498254545142,"score_spread":0.2259503744762115,"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."}}