{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009345477,0.0002108489,0.0002178693,0.0003519731,0.0002786022,0.0002149775,0.00164376,0.00005885655,0.000007210569],"category_scores_gemma":[0.001458161,0.0001485246,0.0000546831,0.00186041,0.0007941715,0.0006820094,0.0001262236,0.0004017571,0.0000223172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004218067,"about_ca_system_score_gemma":0.00006332275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004062074,"about_ca_topic_score_gemma":0.00003044916,"domain_scores_codex":[0.996628,0.0006088737,0.0003179306,0.0009880867,0.0007941813,0.0006628658],"domain_scores_gemma":[0.9990829,0.0001813977,0.0001018583,0.0005311505,0.00001169749,0.00009094515],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004837734,0.0004871875,0.506366,0.00002455314,2.002505e-7,0.0001356291,0.003679536,0.0001626318,0.4661897,0.004060427,0.006464665,0.01238107],"study_design_scores_gemma":[0.0004542763,0.0001596801,0.9533342,0.00002002949,0.000002764566,0.0000647365,0.0004434062,0.0218468,0.00247756,0.004638705,0.01621857,0.0003392521],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9832023,0.000009228492,0.00717557,0.0008392354,0.003163676,0.0003367794,0.000003480489,0.00005688387,0.005212829],"genre_scores_gemma":[0.9881516,0.0000565035,0.0002132119,0.01124972,0.00007813982,0.00004248341,3.501865e-7,0.00001050664,0.0001975041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4637121,"threshold_uncertainty_score":0.6056659,"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."}}