{"id":"W2111893421","doi":"10.1016/j.neuron.2006.08.008","title":"A Synchronization-Desynchronization Code for Natural Communication Signals","year":2006,"lang":"en","type":"article","venue":"Neuron","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":131,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Canadian Institutes of Health Research","keywords":"Synchronization (alternating current); Neuroscience; Context (archaeology); Population; Electroencephalography; Neural activity; Computer science; Code (set theory); Biological neural network; Psychology; Biology; Medicine; Telecommunications","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":[0.0001688513,0.0001660565,0.0001738061,0.0003900141,0.0003391803,0.0005363761,0.0003102598,0.0004715815,0.00269494],"category_scores_gemma":[0.001409642,0.0001386228,0.0002171973,0.0002872654,0.0005624008,0.0006805391,0.0003991975,0.0004372975,0.0003992232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000276623,"about_ca_system_score_gemma":0.0002370306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004595236,"about_ca_topic_score_gemma":0.0006041483,"domain_scores_codex":[0.9999164,0.00001355668,0.000004377574,0.00002952189,0.00002066912,0.00001549069],"domain_scores_gemma":[0.9996736,0.0001192223,0.00005068253,0.00006086981,0.00005721043,0.00003845097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002258516,0.00004828533,0.001466149,0.0000924678,0.0000357326,0.0003021309,0.0003242097,0.02745145,0.2337776,0.6728993,0.003202589,0.06017428],"study_design_scores_gemma":[0.00007389935,0.0001274971,0.007759324,0.00003488049,0.00002992429,0.0007043289,0.00009763538,0.5060738,0.02577237,0.4512994,0.007933531,0.0000933519],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3644394,0.0005753358,0.6095015,0.0009215329,0.0003927391,0.00007252227,0.0004953229,0.0007376926,0.02286394],"genre_scores_gemma":[0.9605836,0.0001620505,0.03479164,0.0001449183,0.0001279747,0.00005342069,0.0001461648,0.0001509303,0.00383918],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00269494,"threshold_uncertainty_score":0.009015441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01820271233900461,"score_gpt":0.2552731367736228,"score_spread":0.2370704244346182,"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."}}