{"id":"W4406729762","doi":"10.1109/telepresence63209.2024.10841535","title":"Mean-Field Representation for EEG Classifications","year":2024,"lang":"en","type":"article","venue":"","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Alberta Innovates","keywords":"Electroencephalography; Computer science; Representation (politics); Field (mathematics); Artificial intelligence; Natural language processing; Pattern recognition (psychology); Mathematics; Psychology; Neuroscience","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":[0.001082225,0.0005079042,0.000541512,0.0011655,0.0002533271,0.0008333907,0.0006779074,0.0008075567,0.003811133],"category_scores_gemma":[0.004068932,0.0001512127,0.0008228481,0.001062025,0.0003289996,0.0009581388,0.0005305773,0.0009464817,0.0007599063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004829508,"about_ca_system_score_gemma":0.0005324318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002429633,"about_ca_topic_score_gemma":0.001739653,"domain_scores_codex":[0.9996124,0.000106086,0.00002846255,0.0001069409,0.0001007696,0.00004528972],"domain_scores_gemma":[0.9992581,0.0003577581,0.00007737987,0.0001011502,0.0001804588,0.0000250992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002777244,0.0001056765,0.002173244,0.0001229057,0.00007441655,0.0001131805,0.0001263609,0.3075688,0.01457455,0.03754206,0.00670981,0.6306113],"study_design_scores_gemma":[0.000005785874,0.00003516274,0.0007128152,0.000008539088,0.000007967499,0.00005726044,0.000009980767,0.982345,0.001573619,0.01416669,0.001066369,0.00001062129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0153153,0.0001488826,0.982641,0.0001362578,0.00004284423,0.00003574652,0.0002442556,0.0005381824,0.0008974847],"genre_scores_gemma":[0.644713,0.0003723401,0.3492613,0.000207179,0.000156336,0.0002619133,0.001249627,0.0001371215,0.003641188],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003811133,"threshold_uncertainty_score":0.01274949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05321702648005261,"score_gpt":0.3374310610384166,"score_spread":0.284214034558364,"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."}}