{"id":"W4207039587","doi":"10.1101/2022.01.21.477243","title":"Time-resolved parameterization of aperiodic and periodic brain activity","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Canada First Research Excellence Fund; Health Canada; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; McGill University","keywords":"Aperiodic graph; Computer science; Spectral density; Artificial neural network; Artificial intelligence; Pattern recognition (psychology); Biological system; Statistical physics; Mathematics; 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":[0.0006094057,0.0003255289,0.0001982961,0.0007386794,0.0001384987,0.0004465324,0.000263822,0.0002828611,0.001097478],"category_scores_gemma":[0.002161435,0.0001431804,0.0002745737,0.00058404,0.0002995578,0.0007113768,0.0004130621,0.0004266463,0.0002172107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001515636,"about_ca_system_score_gemma":0.0001978708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004241612,"about_ca_topic_score_gemma":0.000763225,"domain_scores_codex":[0.9998978,0.00002226354,0.000008552965,0.00003607044,0.00002475952,0.00001047127],"domain_scores_gemma":[0.9995688,0.0001478095,0.00009855274,0.00009172469,0.00006705694,0.00002604935],"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":[0.0007266919,0.0001946417,0.02912048,0.0004798798,0.0001982187,0.0004348197,0.0009993382,0.1072177,0.467916,0.01252146,0.002459137,0.3777317],"study_design_scores_gemma":[0.00002780808,0.0003016966,0.1098117,0.00006076763,0.00006458079,0.001099898,0.0004287368,0.7984611,0.06550683,0.01797003,0.00615702,0.0001099344],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4792842,0.0003413127,0.5177628,0.00009798133,0.00004070824,0.000059258,0.000463952,0.0003819642,0.001567782],"genre_scores_gemma":[0.9081563,0.0002524316,0.089999,0.0000273617,0.00002474287,0.00006840467,0.0005849545,0.0001013489,0.0007853836],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001097478,"threshold_uncertainty_score":0.003671408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01786730411172701,"score_gpt":0.2240241017647098,"score_spread":0.2061567976529828,"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."}}