{"id":"W2049999174","doi":"10.1186/1471-2202-14-s1-p307","title":"How noise correlation impact population code in superior colliculus: an information theoretic approach","year":2013,"lang":"en","type":"article","venue":"BMC Neuroscience","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Queen's University","funders":"","keywords":"Correlation; Computer science; Code (set theory); Noise (video); Population; Inferior colliculus; Superior colliculus; Neuroscience; Theoretical computer science; Psychology; Artificial intelligence; Mathematics; Programming language; Sociology","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":[0.0009940838,0.0004588517,0.0005482628,0.000597314,0.0004186516,0.000778511,0.0008448312,0.0009165456,0.0009100963],"category_scores_gemma":[0.006699267,0.0003992601,0.0006486857,0.0003799187,0.001150292,0.00139022,0.0006041707,0.0006453411,0.00009293256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001641919,"about_ca_system_score_gemma":0.0007949895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005320239,"about_ca_topic_score_gemma":0.003829574,"domain_scores_codex":[0.999611,0.0001369046,0.00001548162,0.00007705161,0.0001113517,0.00004828973],"domain_scores_gemma":[0.9969267,0.002174485,0.0003747779,0.0002071539,0.0002275373,0.00008923753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007644373,0.00005065397,0.003730448,0.00004491474,0.00005342376,0.0001432074,0.00009325562,0.9545986,0.0168721,0.02048902,0.0001790302,0.003668944],"study_design_scores_gemma":[0.000003009013,0.00001536969,0.0008983988,0.000002267126,0.000006835,0.00002023234,0.000008567256,0.9941649,0.001102273,0.003728822,0.00004093564,0.000008353231],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6748159,0.0003381465,0.3203445,0.0007730041,0.0000283493,0.00004681941,0.0002012321,0.0001707291,0.003281326],"genre_scores_gemma":[0.9890745,0.0001056755,0.01032391,0.00004689501,0.0000123478,0.0000237807,0.00005120525,0.00002836904,0.000333281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005320239,"threshold_uncertainty_score":0.011913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05263162324568698,"score_gpt":0.3079399109898501,"score_spread":0.2553082877441631,"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."}}