{"id":"W6903545777","doi":"10.12751/g-node.6953bb","title":"Spike time locking in the electro-sensory system","year":2017,"lang":"en","type":"dataset","venue":"German Neuroinformatics Node","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Electric fish; Neurophysiology; Electroreception; Spike (software development); Line (geometry); Spike train; Electrophysiology","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":[0.0009018605,0.002496494,0.001478253,0.002479862,0.0005465882,0.001768486,0.002545708,0.002491014,0.01411888],"category_scores_gemma":[0.00435668,0.0004325711,0.001787817,0.003060146,0.0004552241,0.0006517389,0.001454086,0.0009915824,0.01921497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009355801,"about_ca_system_score_gemma":0.001801091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01536485,"about_ca_topic_score_gemma":0.03280112,"domain_scores_codex":[0.9992965,0.00009794898,0.00009859959,0.0002471639,0.0001483108,0.0001114076],"domain_scores_gemma":[0.9987888,0.0004848387,0.0001478798,0.0002686259,0.0002168872,0.00009293597],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0007691605,0.0001188881,0.009998549,0.006575023,0.0007836429,0.0003326378,0.00006434367,0.005741513,0.001997439,0.001062878,0.954041,0.01851498],"study_design_scores_gemma":[0.00160026,0.0002029906,0.04552948,0.001527369,0.001015853,0.000866438,0.0001317837,0.008691368,0.00371129,0.005773508,0.9307922,0.0001574085],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002054619,0.0006849052,0.0002680568,0.00007263849,0.00003793969,0.00001562215,0.9957352,0.0005860265,0.0005449869],"genre_scores_gemma":[0.003731391,0.0001835857,0.0003929421,0.00003965314,0.000007908988,0.00006881282,0.9951996,0.00004439717,0.0003316955],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01536485,"threshold_uncertainty_score":0.04723233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02009214772633181,"score_gpt":0.2935651596744996,"score_spread":0.2734730119481678,"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."}}