{"id":"W2963630453","doi":"10.3389/fncom.2014.00123","title":"Structured chaos shapes spike-response noise entropy in balanced neural networks","year":2014,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"National Institute on Drug Abuse","keywords":"Chaotic; Computer science; Spike train; Statistical physics; Entropy (arrow of time); Spike (software development); Network dynamics; ENCODE; Artificial neural network; Artificial intelligence; Physics; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001231581,0.0004017841,0.000727032,0.0007067337,0.0002639169,0.001146654,0.002375926,0.0001445938,0.002355363],"category_scores_gemma":[0.001621435,0.0003449901,0.0001941442,0.001229153,0.0001777064,0.001831288,0.0007027742,0.0006722469,0.00001084946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000995544,"about_ca_system_score_gemma":0.00004831687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001642242,"about_ca_topic_score_gemma":0.00005786455,"domain_scores_codex":[0.9960437,0.001050268,0.0008511104,0.0007415818,0.0006812584,0.0006321204],"domain_scores_gemma":[0.9973714,0.001043509,0.0007408096,0.0004527278,0.0001110487,0.0002805352],"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":[0.001888591,0.0001138313,0.07091933,0.00002146996,0.00001132138,0.00005566482,0.00004431236,0.01741293,0.8941546,0.0002044878,0.00170916,0.0134643],"study_design_scores_gemma":[0.001172243,0.00004398518,0.7437127,0.000120394,0.00002074473,0.00003542476,0.000009553239,0.2014532,0.04783418,0.00330479,0.001812664,0.0004801595],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995611,0.0004858838,0.0009138769,0.0004821825,0.00148472,0.0005738508,0.00002590276,0.00005793897,0.0003647029],"genre_scores_gemma":[0.9966766,0.0009044118,0.00004162348,0.001794442,0.0002916118,0.00003181651,0.000005283338,0.0000568149,0.0001974389],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8463204,"threshold_uncertainty_score":0.9999002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1194656564285822,"score_gpt":0.4644464202671545,"score_spread":0.3449807638385723,"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."}}