{"id":"W4393787874","doi":"10.5281/zenodo.3626141","title":"PERFORM Dataset; one control subject","year":2019,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Subject (documents); Computer science; Control (management); Data mining; Artificial intelligence; World Wide Web","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":[0.001725856,0.002700621,0.001678656,0.001811304,0.001043476,0.001595394,0.002592038,0.002671067,0.06860027],"category_scores_gemma":[0.006909775,0.0004024988,0.001157913,0.001839563,0.0006242579,0.0006315326,0.001992333,0.001263198,0.09105963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006670735,"about_ca_system_score_gemma":0.001737503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009199925,"about_ca_topic_score_gemma":0.01787141,"domain_scores_codex":[0.9984549,0.0003295421,0.0001918126,0.0005538434,0.0002973422,0.0001724731],"domain_scores_gemma":[0.9969566,0.0008730828,0.000161958,0.001075082,0.0007243,0.0002090166],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007959387,0.0002184721,0.001944315,0.001089005,0.000133887,0.000195119,0.00005591053,0.0004479579,0.000986442,0.0004203011,0.9787092,0.01500352],"study_design_scores_gemma":[0.001447295,0.0002035962,0.01321905,0.0004206659,0.0002545212,0.000824641,0.0001496439,0.001563396,0.002552361,0.002710304,0.9765683,0.00008625616],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00230999,0.0003187143,0.001131443,0.0001516367,0.0001805365,0.0001871307,0.9915509,0.001291965,0.002877742],"genre_scores_gemma":[0.003545889,0.00007905073,0.001173486,0.0001231394,0.00003494936,0.000597056,0.9914231,0.000179678,0.002843679],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06860027,"threshold_uncertainty_score":0.2294908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0632380550759229,"score_gpt":0.2779825093119986,"score_spread":0.2147444542360757,"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."}}