{"id":"W2937792970","doi":"10.1088/1741-2552/ab1a95","title":"Assessment of changes in neural activity during acquisition of spatial knowledge using EEG signal classification","year":2019,"lang":"en","type":"article","venue":"Journal of Neural Engineering","topic":"Spatial Cognition and Navigation","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Research and Development Corporation of Newfoundland and Labrador; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Electroencephalography; Task (project management); Computer science; Certainty; Perception; Cognition; Artificial intelligence; Brain activity and meditation; Block (permutation group theory); SIGNAL (programming language); Pattern recognition (psychology); Machine learning; Psychology; Neuroscience; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001789355,0.000119073,0.000275908,0.0003697528,0.00001062432,0.000009497373,0.0000789542,0.00006660615,0.00003759011],"category_scores_gemma":[0.00001314929,0.0001244936,0.00007818492,0.0002283647,0.000008785858,0.0002949629,0.00001545351,0.0002525484,4.934609e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001468766,"about_ca_system_score_gemma":0.00001842952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000135197,"about_ca_topic_score_gemma":0.00000765983,"domain_scores_codex":[0.9991531,0.0000316745,0.0004004574,0.00007512309,0.0002072621,0.0001323512],"domain_scores_gemma":[0.9994817,0.00005522632,0.0002244058,0.00007405312,0.0001209835,0.00004365606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001855867,0.0000228092,0.003153367,0.0001988506,0.00001122791,0.000002145722,0.00005267615,0.3341244,0.6606697,0.000004192594,1.797589e-7,0.001741896],"study_design_scores_gemma":[0.0003878647,0.00007034233,0.2819472,0.0001614152,0.00001107021,0.00001805333,0.00001772053,0.5661146,0.1512074,0.000001205393,8.644103e-7,0.00006223904],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9883646,0.00008243622,0.01087498,0.00001400409,0.0004588396,0.0001368239,0.000003938191,0.00001796625,0.00004643784],"genre_scores_gemma":[0.9993272,0.00001521061,0.000517227,0.000001321988,0.0001124492,0.000002306769,0.000002363798,0.00002056113,0.000001354524],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5094622,"threshold_uncertainty_score":0.50767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02344118395893142,"score_gpt":0.27601651082984,"score_spread":0.2525753268709086,"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."}}