{"id":"W2096845028","doi":"10.1016/s0925-2312(02)00443-5","title":"The role of correlated firing and synchrony in coding information about single and separate objects in cat V1","year":2002,"lang":"en","type":"article","venue":"Neurocomputing","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Stimulus (psychology); Visual cortex; Neuroscience; Coding (social sciences); CATS; Neuronal firing; Computer science; Electrophysiology; Pattern recognition (psychology); Artificial intelligence; Psychology; Mathematics; Cognitive psychology; Statistics","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":[0.0003220703,0.0002509991,0.0002293127,0.0004774614,0.0005453442,0.001111869,0.0004571775,0.0005764618,0.0007917393],"category_scores_gemma":[0.00343159,0.0006003996,0.0003096525,0.0004095415,0.0007755606,0.001202099,0.0009860285,0.000559704,0.0001382335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005494048,"about_ca_system_score_gemma":0.0005049536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003128014,"about_ca_topic_score_gemma":0.003812706,"domain_scores_codex":[0.9998593,0.00002214176,0.00001078646,0.00003503762,0.00003574811,0.0000370356],"domain_scores_gemma":[0.9988697,0.0006028138,0.0001729747,0.00009208004,0.0001168051,0.0001455295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007631596,0.00008575831,0.01808271,0.0001361405,0.00005802687,0.0003643062,0.001243542,0.009552304,0.9319888,0.009743396,0.0002190245,0.027763],"study_design_scores_gemma":[0.0002052512,0.0006088657,0.4008567,0.000117989,0.0001913856,0.001897306,0.001714859,0.3438344,0.2153365,0.03380039,0.001315686,0.0001207324],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884808,0.0002362092,0.009034118,0.0001101166,0.00001832195,0.00001081258,0.00007295421,0.00002894447,0.002007794],"genre_scores_gemma":[0.9983368,0.00005599926,0.001261812,0.00001230179,0.000006177929,0.000004839711,0.00003521091,0.00001692849,0.0002699424],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003128014,"threshold_uncertainty_score":0.006219625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01196685660008661,"score_gpt":0.2024523288654394,"score_spread":0.1904854722653528,"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."}}