{"id":"W3097658797","doi":"10.1371/journal.pcbi.1008302","title":"Tensorpac: An open-source Python toolbox for tensor-based phase-amplitude coupling measurement in electrophysiological brain signals","year":2020,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mila - Quebec Artificial Intelligence Institute; Computer Research Institute of Montréal; Université de Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; CHIST-ERA; Natural Sciences and Engineering Research Council of Canada; Institut de Valorisation des Données; Ministério da Educação; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Canada Research Chairs; Agence Nationale de la Recherche; US-UK Fulbright Commission; Wellcome Trust; Wellcome","keywords":"Python (programming language); Computer science; Toolbox; Spurious relationship; Computation; Computational neuroscience; Software; Computational science; Artificial intelligence; Machine learning; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001850987,0.00230151,0.001468563,0.001820084,0.0006472816,0.00209275,0.003189878,0.0009767746,0.04628212],"category_scores_gemma":[0.008102129,0.001170318,0.001644367,0.001514318,0.00103587,0.00256309,0.003920322,0.002725663,0.02796433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005322618,"about_ca_system_score_gemma":0.003021541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002435963,"about_ca_topic_score_gemma":0.003849429,"domain_scores_codex":[0.9989192,0.0001963816,0.0001271957,0.0002130761,0.0004113311,0.0001328765],"domain_scores_gemma":[0.9976972,0.0008511277,0.0003249405,0.0003696949,0.0005129427,0.0002441088],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001183445,0.0002787811,0.00460172,0.004110429,0.0006896563,0.001102297,0.0009503688,0.03119651,0.04745464,0.03113377,0.5227987,0.3544998],"study_design_scores_gemma":[0.000507001,0.0002592345,0.008861007,0.0006605555,0.0001927179,0.001665645,0.0001952011,0.4791481,0.05478199,0.09516814,0.3579814,0.0005790066],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.003639103,0.0004231877,0.6646367,0.0003268487,0.0001936995,0.0002332581,0.01662668,0.3097738,0.004146753],"genre_scores_gemma":[0.05894558,0.001191989,0.7391307,0.0009621972,0.0002508463,0.002510313,0.04480403,0.1404034,0.01180092],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.04628212,"threshold_uncertainty_score":0.1548291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2197924535544134,"score_gpt":0.3525668946054867,"score_spread":0.1327744410510733,"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."}}