{"id":"W4399262896","doi":"10.1101/2024.05.30.596613","title":"Contextual Expectations in the Real-World Modulate Low-Frequency Neural Oscillations","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Wellcome Trust","keywords":"Electroencephalography; Object (grammar); Psychology; Artificial intelligence; Computer science; Communication; Cognitive psychology; Speech recognition; Pattern recognition (psychology); Computer vision; Neuroscience","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":[0.0001821676,0.0001486874,0.0001250304,0.00008898295,0.00009144549,0.0006680791,0.0001195513,0.0002517097,0.002585212],"category_scores_gemma":[0.001676706,0.0001311923,0.00007322928,0.00008763978,0.0002969554,0.0003336972,0.0004000171,0.0001895261,0.0001646333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001164198,"about_ca_system_score_gemma":0.0000779127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004122169,"about_ca_topic_score_gemma":0.0005357547,"domain_scores_codex":[0.9998708,0.00002448266,0.00001008389,0.00004913663,0.00003163053,0.0000138532],"domain_scores_gemma":[0.9996687,0.0001316344,0.0001118515,0.00003402764,0.00002706125,0.00002663322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0009646934,0.0001200637,0.0196385,0.0002504909,0.00005981021,0.000230449,0.0009673562,0.001118625,0.9571328,0.001386202,0.000450331,0.01768068],"study_design_scores_gemma":[0.00009233828,0.0005631339,0.9147217,0.0000932439,0.00008820791,0.0004254903,0.001044164,0.007098522,0.0665689,0.006726003,0.002536448,0.00004184634],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926523,0.0002113655,0.004494218,0.00007056897,0.00002385593,0.0000154247,0.0001176519,0.00003209285,0.002382391],"genre_scores_gemma":[0.9983571,0.00005110066,0.001166625,0.00003600964,0.000006269902,0.00001207769,0.00004351079,0.00001238089,0.0003148994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002585212,"threshold_uncertainty_score":0.008648336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02972381428151127,"score_gpt":0.2683161098640447,"score_spread":0.2385922955825334,"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."}}