{"id":"W155416283","doi":"10.1007/978-3-319-06740-7_12","title":"A Probabilistic Neural Network Approach for Prediction of Movement and Its Laterality from Deep Brain Local Field Potential","year":2014,"lang":"en","type":"book-chapter","venue":"Advances in intelligent systems and computing","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Artificial intelligence; Computer science; Pattern recognition (psychology); Local field potential; Artificial neural network; Probabilistic neural network; Classifier (UML); Speech recognition; Neuroscience; Psychology; Time delay neural network","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003530243,0.0003043385,0.0005530239,0.00006778226,0.0001068919,0.00007319634,0.0001998758,0.0001768832,0.000003260145],"category_scores_gemma":[0.00006593615,0.000268878,0.00008032327,0.00003076065,0.00009307764,0.00009245686,0.0001902007,0.0002481812,3.764442e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000348758,"about_ca_system_score_gemma":0.000009126737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004186416,"about_ca_topic_score_gemma":0.00001438377,"domain_scores_codex":[0.9979041,0.00009508182,0.0007924791,0.0007148836,0.0002165145,0.000276896],"domain_scores_gemma":[0.9983997,0.0008765392,0.000436581,0.0001765551,0.00004703156,0.00006353038],"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":[0.000210638,0.00006383788,0.0002975306,0.002648706,0.00005527994,0.000008897222,0.0007974609,0.7946662,0.0004774812,0.07963221,0.0001259592,0.1210157],"study_design_scores_gemma":[0.0002482912,0.0004043943,0.00002103616,0.0009574252,0.00002305452,0.00001399402,0.00005097281,0.9866847,0.0006745777,0.007702815,0.002983461,0.0002352165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01945447,0.008532707,0.9653994,0.00004844867,0.002003281,0.001625549,0.0001066619,0.00005911845,0.002770386],"genre_scores_gemma":[0.9971759,0.0002141177,0.0006049531,0.0002638104,0.0006111088,0.00002330829,0.0000267213,0.00002732279,0.001052772],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9777214,"threshold_uncertainty_score":0.9999763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02555790898899726,"score_gpt":0.2565802688278908,"score_spread":0.2310223598388935,"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."}}