{"id":"W2401626140","doi":"","title":"Treating Epilepsy by Reinforcement Learning Via Manifold-Based Simulation.","year":2010,"lang":"en","type":"article","venue":"National Conference on Artificial Intelligence","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Reinforcement learning; Computer science; Epilepsy; Artificial intelligence; Manifold (fluid mechanics); Psychology; Neuroscience; Engineering; Mechanical engineering","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":[0.00027643,0.0003910838,0.0004432909,0.0002000959,0.0002041348,0.0003887068,0.0005292804,0.0005292696,0.001785157],"category_scores_gemma":[0.001353975,0.000146618,0.0003517143,0.0001034659,0.000397714,0.0003832112,0.0007662417,0.0006984071,0.0002246163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002931958,"about_ca_system_score_gemma":0.0005557659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001923398,"about_ca_topic_score_gemma":0.001997404,"domain_scores_codex":[0.9999268,0.00003011633,0.000004522442,0.00001007097,0.00001594982,0.00001250345],"domain_scores_gemma":[0.9997441,0.000155894,0.00003042088,0.00001784935,0.00002313151,0.00002859748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001993006,0.00009996515,0.0008522983,0.00007188405,0.00005683986,0.0002218242,0.0000552573,0.9406993,0.00387323,0.006346501,0.001973646,0.04554991],"study_design_scores_gemma":[0.00003928023,0.00008465795,0.0001234002,0.00001033973,0.00001343133,0.00008234633,0.00001034069,0.991652,0.0008425227,0.006360328,0.000775597,0.000005817665],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07428475,0.001757707,0.9107772,0.001940186,0.0002144379,0.0001612481,0.0000823591,0.0008038745,0.009978224],"genre_scores_gemma":[0.9645454,0.0005072891,0.03330345,0.0001042425,0.00002731445,0.0001232403,0.00003663694,0.0000324365,0.001320051],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001923398,"threshold_uncertainty_score":0.005971968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06475144094737749,"score_gpt":0.329147666545675,"score_spread":0.2643962255982975,"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."}}