{"id":"W3133302233","doi":"10.1101/2021.02.18.431851","title":"Burst coding despite unimodal interval distributions","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Burstiness; Neural coding; Coding (social sciences); Spike (software development); Salient; Computer science; Bivariate analysis; Interval (graph theory); Information transmission; Information theory; Probability distribution; Pattern recognition (psychology); Artificial intelligence; Statistics; Mathematics; Machine learning","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":[0.0006742943,0.000195892,0.0003647001,0.0005763414,0.0002402969,0.001074446,0.0005841519,0.0003664283,0.001201755],"category_scores_gemma":[0.007258426,0.0001938226,0.0002281583,0.0004334879,0.000974696,0.001461575,0.0006884102,0.0007193146,0.0002281035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004448299,"about_ca_system_score_gemma":0.0003995999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007455173,"about_ca_topic_score_gemma":0.0004945071,"domain_scores_codex":[0.9996774,0.00005714079,0.0000261365,0.00008875157,0.0000887956,0.0000617788],"domain_scores_gemma":[0.995919,0.002199048,0.000594143,0.0006742539,0.0003539525,0.0002596247],"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":[0.001210063,0.0001523284,0.02951001,0.0004415315,0.0001293083,0.0009241826,0.001454632,0.2304752,0.3362086,0.2859147,0.002172461,0.1114069],"study_design_scores_gemma":[0.00003842678,0.0001011652,0.01534207,0.00003089269,0.00002982558,0.0004505471,0.0001586987,0.765927,0.0313766,0.1856401,0.0008517826,0.00005290001],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7944286,0.000226825,0.1995823,0.0002597424,0.00002798441,0.00001608601,0.000258905,0.0003940893,0.004805511],"genre_scores_gemma":[0.9928278,0.00004437207,0.006687076,0.00002688509,0.000008449994,0.000009353487,0.00006037767,0.00004361791,0.000292036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001201755,"threshold_uncertainty_score":0.004020274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02506672982125554,"score_gpt":0.2351315203971399,"score_spread":0.2100647905758843,"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."}}