{"id":"W1983669930","doi":"10.1152/jn.00256.2010","title":"Neural Heterogeneity and Efficient Population Codes for Communication Signals","year":2010,"lang":"en","type":"article","venue":"Journal of Neurophysiology","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":137,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Canadian Institutes of Health Research","keywords":"Neural coding; Sensory system; Population; Neuroscience; ENCODE; Coding (social sciences); Encoding (memory); Courtship; Computer science; Biology; Mathematics","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":[0.0001995987,0.0001514137,0.0002535119,0.000375677,0.0001950522,0.0005533973,0.0003649782,0.0002788736,0.0007315386],"category_scores_gemma":[0.001815671,0.0001793541,0.0001731323,0.0001875331,0.0005326584,0.0008479398,0.0005256693,0.0004054505,0.0001695129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003471404,"about_ca_system_score_gemma":0.0001780525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000335578,"about_ca_topic_score_gemma":0.0003524944,"domain_scores_codex":[0.9998145,0.00002664292,0.00001340264,0.00004597932,0.0000591966,0.00004041449],"domain_scores_gemma":[0.9990055,0.0004563338,0.0002000021,0.0001476034,0.0001186749,0.00007195929],"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":[0.000184431,0.00003052213,0.005886798,0.00006569421,0.00002401456,0.0001948747,0.0001828121,0.01314801,0.9441681,0.01127973,0.0001159722,0.02471903],"study_design_scores_gemma":[0.00009193717,0.0004750252,0.1413402,0.00002890218,0.00007117489,0.001873767,0.0003626935,0.3072882,0.5064458,0.03880452,0.003104175,0.0001136061],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9412479,0.0001732734,0.0564617,0.00006796345,0.000006324794,0.00001354724,0.00005226307,0.00008027297,0.001896669],"genre_scores_gemma":[0.9924292,0.00005876449,0.00711792,0.00001170388,0.000006227528,0.00001362772,0.00004244864,0.00001905293,0.0003009997],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007315386,"threshold_uncertainty_score":0.002518654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03357434020852021,"score_gpt":0.2968791263046166,"score_spread":0.2633047860960964,"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."}}