{"id":"W3195389227","doi":"10.1038/s41597-021-01007-5","title":"MNI-FTD templates, unbiased average templates of frontotemporal dementia variants","year":2021,"lang":"en","type":"article","venue":"Scientific Data","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Douglas Mental Health University Institute; McGill University; Centres Intégré Universitaires de Santé et de Services Sociaux; Montreal Neurological Institute and Hospital","funders":"National Institute on Aging; Alzheimer Society Research Program; University of California, San Francisco; Canadian Institutes of Health Research; University of Southern California; Alzheimer Society; National Institutes of Health; Consortium canadien en neurodégénérescence associée au vieillissement; Sanofi","keywords":"Frontotemporal dementia; Template; Computer science; Atrophy; Semantic dementia; Neuroimaging; Dementia; Probabilistic logic; Artificial intelligence; Medicine; Biology; Neuroscience; Pathology; Disease","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002073673,0.001294337,0.0007046494,0.002452821,0.0009444629,0.001758739,0.001494294,0.0009312943,0.01263621],"category_scores_gemma":[0.009552224,0.0006790868,0.00108961,0.002392686,0.0005107112,0.001051944,0.001357564,0.000883168,0.004210009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009332449,"about_ca_system_score_gemma":0.001952924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01545892,"about_ca_topic_score_gemma":0.03329851,"domain_scores_codex":[0.9991462,0.0001600021,0.0001391332,0.0003017151,0.0001923289,0.00006060526],"domain_scores_gemma":[0.9988154,0.0002467207,0.0002168309,0.0003852897,0.000288984,0.00004678327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000954218,0.0001815618,0.04415408,0.001271886,0.001325941,0.001838941,0.001764006,0.01815899,0.06078208,0.04000604,0.1813039,0.6482584],"study_design_scores_gemma":[0.0003881445,0.0005437941,0.2346516,0.0005957824,0.001101267,0.01525263,0.0008105588,0.08955916,0.09470806,0.1153755,0.4466147,0.0003988194],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07741573,0.002223645,0.8366053,0.0005415194,0.0003751435,0.001110511,0.05101201,0.01370295,0.01701328],"genre_scores_gemma":[0.2183158,0.001022472,0.7086421,0.0003084377,0.0001084976,0.003094695,0.05370722,0.005040801,0.009759972],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01545892,"threshold_uncertainty_score":0.04227233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07653904424421291,"score_gpt":0.3469934429536982,"score_spread":0.2704543987094853,"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."}}