{"id":"W2012351639","doi":"10.1115/imece2012-88371","title":"Inertial Sensor Dynamics, Selection and Applications for Epileptic Seizure Detection","year":2012,"lang":"en","type":"article","venue":"","topic":"Neurological disorders and treatments","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Research Council Canada","keywords":"Computer science; Noise (video); Wearable computer; MATLAB; Acceleration; Simulated annealing; Inertial measurement unit; Inertial frame of reference; Control theory (sociology); Simulation; Algorithm; Artificial intelligence; Embedded system; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002048064,0.000429257,0.0003193738,0.0002428172,0.0001933265,0.0002718403,0.0003208469,0.0003921351,0.0009256001],"category_scores_gemma":[0.0007315048,0.0002834266,0.0001852148,0.0002384946,0.0002632923,0.0004425489,0.0002792793,0.0001759875,0.000243359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002777814,"about_ca_system_score_gemma":0.0002985636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008940425,"about_ca_topic_score_gemma":0.001443386,"domain_scores_codex":[0.9998686,0.00003485036,0.000006795306,0.00002919681,0.00005055343,0.000009963612],"domain_scores_gemma":[0.9998715,0.00004661101,0.00003123936,0.00001471879,0.00002974758,0.000006192244],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001922637,0.00006666416,0.002153113,0.0001584967,0.00002651636,0.0002236739,0.0001713653,0.7148231,0.1113963,0.01351445,0.001089737,0.1561843],"study_design_scores_gemma":[0.000008409438,0.0001063936,0.001131948,0.0000105276,0.0000106227,0.0001076194,0.00005107574,0.9782683,0.01487944,0.003391269,0.002018895,0.00001551362],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04635433,0.0004529683,0.949501,0.000231231,0.00003276165,0.00003022223,0.00002303079,0.0002738102,0.00310066],"genre_scores_gemma":[0.8341604,0.0004260697,0.1634223,0.00003751474,0.00002135431,0.00004687679,0.00002922944,0.00002993607,0.001826339],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009256001,"threshold_uncertainty_score":0.003096461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01239064222200886,"score_gpt":0.2656185585602861,"score_spread":0.2532279163382772,"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."}}