{"id":"W4323031759","doi":"10.1371/journal.pcbi.1010938","title":"Coding of object location by heterogeneous neural populations with spatially dependent correlations in weakly electric fish","year":2023,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Fish biology, ecology, and behavior","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research","keywords":"Receptive field; Electric fish; Sensory system; ENCODE; Neuroscience; Electroreception; Neural coding; Coding (social sciences); Biology; Computer science; Fish <Actinopterygii>; Mathematics; Gene","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":[0.0001393547,0.0001040082,0.0001446342,0.0001434664,0.0001160626,0.0001790723,0.0002170253,0.0001483627,0.0002972437],"category_scores_gemma":[0.0007223286,0.0001492032,0.0001614616,0.0001220997,0.0003865897,0.0002805761,0.0003653616,0.000175487,0.00003110227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002048758,"about_ca_system_score_gemma":0.0001359067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001112627,"about_ca_topic_score_gemma":0.001912023,"domain_scores_codex":[0.9999472,0.000009266444,0.000004010628,0.00001680739,0.00001174971,0.00001083728],"domain_scores_gemma":[0.999815,0.00008131802,0.00004709532,0.00001765956,0.00001828244,0.00002063376],"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":[0.0001497219,0.00001852331,0.01217241,0.00003818477,0.00003518223,0.0001761018,0.0001781946,0.02068634,0.9585702,0.001250085,0.0000378472,0.006687295],"study_design_scores_gemma":[0.00007971785,0.0002865602,0.2881427,0.00001625868,0.00009388536,0.0004315225,0.0003575467,0.5388582,0.1632894,0.007938177,0.0004349997,0.00007101926],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898543,0.00002113497,0.009833761,0.00002005868,0.000001258771,0.000003940145,0.00001743897,0.00001133343,0.0002367053],"genre_scores_gemma":[0.9979216,0.00001232656,0.001956003,0.000005252714,9.654749e-7,0.000004828848,0.00001104952,0.000003164466,0.00008482684],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001112627,"threshold_uncertainty_score":0.002212346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02660187366545141,"score_gpt":0.2581467925084807,"score_spread":0.2315449188430292,"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."}}