{"id":"W4293463901","doi":"10.1038/s41597-022-01645-3","title":"Probabilistic atlas for the language network based on precision fMRI data from >800 individuals","year":2022,"lang":"en","type":"article","venue":"Scientific Data","topic":"Neurobiology of Language and Bilingualism","field":"Neuroscience","cited_by":149,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Institute on Deafness and Other Communication Disorders; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Simons Foundation; U.S. Department of Health and Human Services","keywords":"Interpretability; Computer science; Probabilistic logic; Voxel; Artificial intelligence; Atlas (anatomy); Natural language processing; Machine learning","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":["sts","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003812303,0.0001922011,0.0001935484,0.00008518193,0.001889285,0.0004258874,0.008466874,0.00004591345,0.001042277],"category_scores_gemma":[0.004645573,0.0001300051,0.00004976859,0.0006678541,0.0004442385,0.0002681763,0.005414604,0.0003387108,0.0001263958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002576551,"about_ca_system_score_gemma":0.0001786279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004242078,"about_ca_topic_score_gemma":0.00009051144,"domain_scores_codex":[0.99581,0.0005447887,0.0003229268,0.002095629,0.0007260007,0.0005006321],"domain_scores_gemma":[0.987832,0.004535615,0.0001895036,0.007341943,0.0000250839,0.00007585898],"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":[0.0001457453,0.0003065275,0.00008470214,0.00001404157,0.00001253573,0.0001273673,0.000624458,0.002871561,0.03028375,0.00013733,0.9543848,0.0110072],"study_design_scores_gemma":[0.0008489689,0.0001883495,0.0001607483,0.00003112701,0.00009575768,0.0000278196,0.0003216905,0.128249,0.004507177,0.001502931,0.86371,0.0003564466],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5920334,0.001285954,0.001790199,0.007423733,0.02106487,0.005578937,0.3691697,0.0004982649,0.001154934],"genre_scores_gemma":[0.9304355,0.000006731306,0.001777603,0.006265074,0.001032377,0.0001829122,0.05547073,0.0000625001,0.004766524],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3384021,"threshold_uncertainty_score":0.9998709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1205485106440618,"score_gpt":0.3402758178060862,"score_spread":0.2197273071620243,"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."}}