{"id":"W2042524814","doi":"10.1109/iembs.2011.6091861","title":"Epileptic seizure prediction using variational mixture of Gaussians","year":2011,"lang":"en","type":"article","venue":"","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver General Hospital; University of British Columbia","funders":"","keywords":"Ictal; Electroencephalography; Pattern recognition (psychology); Histogram; Epileptic seizure; Constant false alarm rate; False alarm; Artificial intelligence; Sensitivity (control systems); Computer science; Mixture model; Mathematics; Speech recognition; Psychology; Image (mathematics)","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":[0.0008566223,0.0006504609,0.0008700938,0.0006227199,0.000168456,0.0004650652,0.0009236962,0.0006026266,0.0004667155],"category_scores_gemma":[0.002126911,0.0004882481,0.0007332084,0.0004716024,0.0003018029,0.0004985264,0.0005558647,0.00068293,0.0002073688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004385601,"about_ca_system_score_gemma":0.0006470475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009713947,"about_ca_topic_score_gemma":0.009059968,"domain_scores_codex":[0.9996902,0.000114329,0.00001732568,0.00007443688,0.0000659517,0.00003792785],"domain_scores_gemma":[0.9994388,0.0003605716,0.00005121983,0.00003713512,0.00008557648,0.00002664096],"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":[0.0001987897,0.00005441999,0.005190431,0.00004604781,0.000160757,0.0001080827,0.00005998097,0.862327,0.005754759,0.003824337,0.001417243,0.1208583],"study_design_scores_gemma":[0.000002011602,0.000004440976,0.0001730427,7.552808e-7,0.00000217368,0.00000583959,0.000001125916,0.9990602,0.0001751443,0.0005166064,0.00005631849,0.000002334376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03584929,0.0003568924,0.9626321,0.000166731,0.00002854308,0.00002205083,0.00008360731,0.0005309356,0.0003298203],"genre_scores_gemma":[0.8025565,0.0003355661,0.1948516,0.0001030414,0.00006656752,0.00005569159,0.0004457101,0.0001076164,0.001477772],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009713947,"threshold_uncertainty_score":0.01931483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05643015137935364,"score_gpt":0.2597269047827792,"score_spread":0.2032967534034255,"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."}}