{"id":"W2109248993","doi":"10.1016/j.mbs.2003.08.012","title":"Coding of information in models of tuberous electroreceptors","year":2003,"lang":"en","type":"article","venue":"Mathematical Biosciences","topic":"Fish biology, ecology, and behavior","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Electroreception; Electric fish; Stimulus (psychology); Decoding methods; Computer science; Biological system; Neuroscience; Biology; Algorithm; Sensory system; Fish <Actinopterygii>","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005450448,0.00006226109,0.0001550077,0.00005735267,0.00002755463,0.000005586633,0.0001776574,0.00006142096,0.0005911088],"category_scores_gemma":[0.0001884909,0.00004527027,0.00002837962,0.0003381718,0.0005576753,0.0003776223,0.00003627336,0.00004926433,0.00004508817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003126313,"about_ca_system_score_gemma":0.00001163902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000335635,"about_ca_topic_score_gemma":0.00003266575,"domain_scores_codex":[0.9991818,0.00003990933,0.0003259436,0.00009957787,0.0001681798,0.0001845867],"domain_scores_gemma":[0.9997016,0.00007293464,0.00009980729,0.00008624182,0.000006621508,0.0000327687],"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":[0.00003117642,0.001495903,0.275004,0.0002202645,0.000009692923,0.000001818847,0.004874829,0.00148821,0.4906289,0.2167049,0.0004347102,0.009105649],"study_design_scores_gemma":[0.001015777,0.001337045,0.2254178,0.0001120276,0.00003602812,0.00004557682,0.003448854,0.02505488,0.3956632,0.3467629,0.0004509817,0.0006548631],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9794155,0.000005030755,0.00162244,0.00005167872,0.00004519566,0.0001181966,0.000002080424,0.000006777738,0.0187331],"genre_scores_gemma":[0.994979,0.00000548966,0.004953884,0.00003276338,9.664856e-7,0.000006516792,4.716046e-7,0.000001264787,0.00001965365],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.130058,"threshold_uncertainty_score":0.6472227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01825135523071257,"score_gpt":0.2416730584007797,"score_spread":0.2234217031700672,"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."}}