{"id":"W4293463483","doi":"10.1038/s41597-022-01625-7","title":"Le Petit Prince multilingual naturalistic fMRI corpus","year":2022,"lang":"en","type":"article","venue":"Scientific Data","topic":"Neurobiology of Language and Bilingualism","field":"Neuroscience","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Office of Naval Research; National Institute on Aging; Multidisciplinary University Research Initiative; Jiangsu University; National Institutes of Health; National Science Foundation; Jiangsu Normal University; New York University Abu Dhabi; Agence Nationale de la Recherche","keywords":"Functional magnetic resonance imaging; Generalizability theory; Computer science; Psychology; Active listening; Functional neuroimaging; Neuroimaging; Cognitive neuroscience; Cognitive psychology; Cognition; Communication","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":[0.0009392035,0.0009642486,0.0005125827,0.001362224,0.001304233,0.0008534177,0.0009572657,0.001196866,0.01385338],"category_scores_gemma":[0.003391991,0.0004019436,0.0003640783,0.0009336775,0.0009891518,0.0005319975,0.001481296,0.0008840882,0.003757866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006197459,"about_ca_system_score_gemma":0.0009647944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0157183,"about_ca_topic_score_gemma":0.02537801,"domain_scores_codex":[0.9994087,0.0001967826,0.00006728961,0.0001773824,0.00009889311,0.00005092198],"domain_scores_gemma":[0.9979941,0.0008924864,0.0001290808,0.0004498772,0.0003903393,0.000144127],"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":[0.006545268,0.001807518,0.02357392,0.007034981,0.0007546007,0.03347079,0.01710855,0.004084281,0.2230298,0.009890283,0.3826358,0.2900642],"study_design_scores_gemma":[0.001162618,0.0006061925,0.2299417,0.0004727583,0.0002794591,0.03996434,0.003637141,0.00517227,0.02981995,0.004230253,0.6843551,0.0003582366],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.6880161,0.003818911,0.02742459,0.001953038,0.0003695118,0.002639937,0.2348715,0.003437937,0.03746862],"genre_scores_gemma":[0.6013915,0.001041095,0.05481595,0.001123496,0.0003244308,0.008941431,0.3078174,0.001437374,0.02310735],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.0157183,"threshold_uncertainty_score":0.04634416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07188631091391356,"score_gpt":0.31624786866279,"score_spread":0.2443615577488764,"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."}}