{"id":"W4376876719","doi":"10.7554/elife.85786","title":"Pynapple, a toolbox for data analysis in neuroscience","year":2023,"lang":"en","type":"article","venue":"eLife","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Azrieli Foundation; Israel Science Foundation; Natural Sciences and Engineering Research Council of Canada; Institut de science ouverte Tanenbaum; International Development Research Centre","keywords":"Python (programming language); Computer science; Toolbox; Neuroinformatics; Data type; Data mining; Artificial intelligence; Data science; Programming language","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":[0.000390924,0.00007380728,0.0001216719,0.0003085296,0.00009987465,0.00006493259,0.000448929,0.00002553378,0.00001015005],"category_scores_gemma":[0.001494977,0.00006612541,0.00004801712,0.003259674,0.00004430486,0.0002316945,0.0001867022,0.00007070268,0.00004939987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000117869,"about_ca_system_score_gemma":0.0000228458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002970717,"about_ca_topic_score_gemma":0.0001206812,"domain_scores_codex":[0.998701,0.00003738497,0.0001601928,0.0005961088,0.0002423347,0.0002630099],"domain_scores_gemma":[0.9991022,0.0002547289,0.00004416082,0.0005383232,0.00001305362,0.00004753587],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000915208,0.000154086,0.02149587,0.00003224027,0.0000117367,0.0001232193,0.0001391348,0.009577187,0.9193122,0.01074177,0.02653761,0.01178342],"study_design_scores_gemma":[0.0001992683,0.00004302004,0.04193079,0.000002141624,0.00001995002,0.000002261803,0.00001071675,0.9226154,0.004033444,0.0002590029,0.03077076,0.0001132549],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879468,0.000005825669,0.007276201,0.002431683,0.0008024786,0.0004020278,0.0002756018,0.000222346,0.0006370302],"genre_scores_gemma":[0.9959875,0.00003282915,0.0001229451,0.002451678,0.00004983004,0.00002905644,0.00006667135,0.000009382909,0.001250127],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9152787,"threshold_uncertainty_score":0.2696516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1528217409520327,"score_gpt":0.3524358714671734,"score_spread":0.1996141305151408,"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."}}