{"id":"W4221076233","doi":"10.1101/2022.03.06.483177","title":"LanA (Language Atlas): A probabilistic atlas for the language network based on fMRI data from &gt;800 individuals","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Neurobiology of Language and Bilingualism","field":"Neuroscience","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Simons Center for the Social Brain, Massachusetts Institute of Technology; McGovern Institute for Brain Research, Massachusetts Institute of Technology; National Institutes of Health; Simons Foundation","keywords":"Interpretability; Computer science; Atlas (anatomy); Probabilistic logic; Artificial intelligence; Natural language processing; Functional magnetic resonance imaging; Machine learning; Psychology; Neuroscience","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":[0.001995211,0.0005993354,0.0006376231,0.00286684,0.0006450776,0.00184911,0.001204903,0.0009833698,0.02927834],"category_scores_gemma":[0.004624327,0.0008241193,0.0009248644,0.002657561,0.0006358915,0.0009389095,0.001435066,0.001107966,0.005616395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009363457,"about_ca_system_score_gemma":0.001903519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006938168,"about_ca_topic_score_gemma":0.01248107,"domain_scores_codex":[0.9993715,0.0002193064,0.00005960977,0.0001865795,0.0001136325,0.00004945581],"domain_scores_gemma":[0.9984336,0.0007502998,0.0002639873,0.0003208826,0.0001723195,0.0000588186],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002007463,0.0002227235,0.02466585,0.003187683,0.001066534,0.001568011,0.003066721,0.05899517,0.09363705,0.06008318,0.3556061,0.3958935],"study_design_scores_gemma":[0.0005156669,0.0004475473,0.1267344,0.0005716836,0.0007411274,0.005874576,0.000599125,0.1689934,0.04155783,0.09580479,0.5576804,0.0004793823],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05438888,0.001234728,0.7813767,0.0009179735,0.0001789993,0.0005605637,0.1183072,0.02511166,0.01792344],"genre_scores_gemma":[0.2642382,0.0008619311,0.656241,0.0003261951,0.0001007976,0.003657425,0.05442937,0.00983628,0.01030872],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02927834,"threshold_uncertainty_score":0.09794581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03967723197372144,"score_gpt":0.2764462041290968,"score_spread":0.2367689721553753,"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."}}