{"id":"W2105920505","doi":"10.3389/fnins.2014.00228","title":"Gender differences in the temporal voice areas","year":2014,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Neuroscience and Music Perception","field":"Neuroscience","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; McGill University; International Laboratory for Brain, Music and Sound Research","funders":"Biotechnology and Biological Sciences Research Council; Agence Nationale de la Recherche","keywords":"Superior temporal gyrus; Statistical parametric mapping; Middle temporal gyrus; Univariate; Psychology; Perception; Audiology; Temporal lobe; Multivariate analysis; Multivariate statistics; Functional connectivity; Pattern analysis; Multivariate analysis of variance; Bivariate analysis; Functional magnetic resonance imaging; Computer science; Neuroscience; Medicine; Artificial intelligence; Statistics; Mathematics; Magnetic resonance imaging","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":[0.0005027312,0.000279514,0.0002516624,0.0004591468,0.0001523789,0.0003688765,0.0001503524,0.0001769004,0.01089337],"category_scores_gemma":[0.002118808,0.0001111045,0.0002332982,0.0001301108,0.0002940379,0.0002907066,0.000248438,0.0001494721,0.00101336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001008512,"about_ca_system_score_gemma":0.0001065845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004436833,"about_ca_topic_score_gemma":0.001049507,"domain_scores_codex":[0.9997624,0.00003609617,0.00002651598,0.00009013031,0.00004881568,0.00003612296],"domain_scores_gemma":[0.9993576,0.0002896967,0.0001261377,0.00006148636,0.00009327837,0.00007175963],"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":[0.00352079,0.0001290929,0.1410461,0.00047101,0.0002720374,0.001767967,0.003450939,0.0003656283,0.6955998,0.002214501,0.001258795,0.1499033],"study_design_scores_gemma":[0.00004339214,0.0006529639,0.9710138,0.00003430035,0.00009199205,0.002558413,0.0008331132,0.0008039463,0.01915756,0.001828957,0.002958926,0.00002269512],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9845333,0.0011251,0.005742769,0.0001306232,0.0001110311,0.00003961692,0.0006974919,0.00004456809,0.007575418],"genre_scores_gemma":[0.9964084,0.0001572105,0.000948608,0.00006364811,0.00002633402,0.00002819462,0.000137497,0.00003224416,0.002197826],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01089337,"threshold_uncertainty_score":0.03644198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06056124735127242,"score_gpt":0.2730208831394814,"score_spread":0.212459635788209,"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."}}