{"id":"W2767802697","doi":"10.1111/epi.13905","title":"Methodological standards and functional correlates of depth in vivo electrophysiological recordings in control rodents. A <scp>TASK</scp>1‐<scp>WG</scp>3 report of the <scp>AES</scp>/<scp>ILAE</scp> Translational Task Force of the ILAE","year":2017,"lang":"en","type":"article","venue":"Epilepsia","topic":"Neuroscience and Neuropharmacology Research","field":"Neuroscience","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"National Institute of Neurological Disorders and Stroke; Natural Sciences and Engineering Research Council of Canada; National Institute for Health and Care Research; Canadian Institutes of Health Research; U.S. Department of Defense; Fundação de Amparo à Pesquisa do Estado de São Paulo; GlaxoSmithKline Japan","keywords":"In vivo; Electrophysiology; Task (project management); Neuroscience; Pharmacology; Medicine; Psychology; Biology; Engineering; Biotechnology","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":["metaresearch","metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.00405034,0.0005722277,0.0012509,0.0003663661,0.0007653855,0.0001128577,0.001956405,0.0004620973,0.00002395692],"category_scores_gemma":[0.05062075,0.0003792808,0.0005004631,0.001145827,0.003349656,0.0005482346,0.0006599062,0.001802303,0.000005737688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001013949,"about_ca_system_score_gemma":0.0006490569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005457054,"about_ca_topic_score_gemma":0.00003565921,"domain_scores_codex":[0.9910637,0.002564369,0.001529679,0.001551526,0.002018091,0.001272636],"domain_scores_gemma":[0.9800552,0.0167577,0.001513182,0.001050826,0.0003707199,0.000252353],"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":[0.00008559629,0.0003870957,0.1602866,0.00005133255,0.00002604094,0.0001465469,0.0004295169,0.0004904513,0.834702,0.0006444262,0.002624144,0.000126245],"study_design_scores_gemma":[0.002428135,0.0008504994,0.5526711,0.00007940351,0.00006441405,0.0003060775,0.0001953155,0.002138695,0.4360944,0.00268643,0.002435943,0.00004952415],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944584,0.0001757195,0.0003948997,0.0003124631,0.0009418082,0.001380584,0.0003315107,0.00004344379,0.001961159],"genre_scores_gemma":[0.9966172,0.0004062204,0.00009459379,0.0005933339,0.0001160424,0.000128649,0.000003939594,0.00004773754,0.001992275],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3986075,"threshold_uncertainty_score":0.9998659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07508942112769543,"score_gpt":0.3489755964312511,"score_spread":0.2738861753035557,"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."}}