{"id":"W3185588896","doi":"10.1101/2021.07.28.454040","title":"The universal language network: A cross-linguistic investigation spanning 45 languages and 12 language families","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Neurobiology of Language and Bilingualism","field":"Neuroscience","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Institute on Deafness and Other Communication Disorders; McGovern Institute for Brain Research, Massachusetts Institute of Technology; National Institutes of Health; Simons Center for the Social Brain, Massachusetts Institute of Technology; Cognitive Neuroscience Society","keywords":"Computer science; Variation (astronomy); Linguistics; Lateralization of brain function; Psychology; Cognitive psychology","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":[0.0004502798,0.0001248958,0.0002259338,0.001279811,0.0003478274,0.0005607436,0.0001734768,0.0001350201,0.002186652],"category_scores_gemma":[0.0008997207,0.00009548035,0.000165957,0.0008027259,0.0006928672,0.00071951,0.001094055,0.0002169398,0.0001494945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002562936,"about_ca_system_score_gemma":0.0002558083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002701929,"about_ca_topic_score_gemma":0.003703266,"domain_scores_codex":[0.9997671,0.0000518207,0.00001297706,0.00009843872,0.00002668888,0.00004294035],"domain_scores_gemma":[0.9994664,0.0001705295,0.0001158108,0.00006788437,0.0000839822,0.00009546363],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001286466,0.0001262864,0.545175,0.0004740387,0.0005650859,0.00188973,0.007469345,0.003533298,0.294183,0.008623856,0.0008375644,0.1358363],"study_design_scores_gemma":[0.00001972026,0.0001607431,0.9706163,0.00004584315,0.0001533809,0.002273369,0.002620425,0.004925596,0.008971298,0.006469602,0.00371906,0.00002471303],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970224,0.0001952939,0.001463517,0.00001818801,0.000001082719,0.000004580563,0.0001810617,0.00001756331,0.001096311],"genre_scores_gemma":[0.99887,0.00005803325,0.0007909076,0.000008979451,0.00000108131,0.000006227618,0.0001215923,0.000007908792,0.000135411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002701929,"threshold_uncertainty_score":0.007315099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01675635350756757,"score_gpt":0.2632263018116438,"score_spread":0.2464699483040762,"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."}}