{"id":"W2079848144","doi":"10.1016/j.jalz.2010.05.569","title":"P1‐022: Characterizing abnormal white matter structure in primary progressive aphasia","year":2010,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Western Hospital; Toronto Rehabilitation Institute; Sunnybrook Health Science Centre; Health Sciences Centre; University Health Network; University of Toronto","funders":"","keywords":"Primary progressive aphasia; Diffusion MRI; White matter; Fractional anisotropy; Audiology; Arcuate fasciculus; Voxel; Nuclear medicine; Uncinate fasciculus; SMA*; Psychology; Boston Naming Test; Inferior longitudinal fasciculus; Medicine; Neuroscience; Dementia; Cognition; Pathology; Radiology; Neuropsychology; Mathematics; Magnetic resonance imaging; Frontotemporal dementia; Disease","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005138374,0.000704408,0.0003753242,0.001714466,0.0004242031,0.0006539075,0.0003520128,0.0005892827,0.004063307],"category_scores_gemma":[0.001125117,0.0002101699,0.0001740517,0.0006351843,0.0004993555,0.0003585571,0.000369379,0.0002640301,0.0009756344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002281755,"about_ca_system_score_gemma":0.0002824008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001872348,"about_ca_topic_score_gemma":0.002291773,"domain_scores_codex":[0.9998556,0.0000207286,0.00001931322,0.00004430734,0.00003917634,0.00002077356],"domain_scores_gemma":[0.9997961,0.00004493666,0.00004549407,0.00001735083,0.00003770253,0.00005847301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004356249,0.0007705287,0.6270168,0.0004973468,0.0001940886,0.03667513,0.001360458,0.0004520706,0.2611554,0.0003799583,0.002993842,0.06414824],"study_design_scores_gemma":[0.00007406887,0.001388891,0.9573022,0.00001992107,0.00004450908,0.03193359,0.0002331878,0.0009433615,0.00648854,0.0002722887,0.001287936,0.00001149451],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996058,0.0001560277,0.0006881879,0.00004516665,0.000007047399,0.0001068225,0.0003297394,0.00004266313,0.002566411],"genre_scores_gemma":[0.9969469,0.0001105231,0.001078659,0.00003832028,0.00001785006,0.00005883511,0.0004672377,0.00002104535,0.001260619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004063307,"threshold_uncertainty_score":0.01359314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02388996777428627,"score_gpt":0.3067111616228843,"score_spread":0.282821193848598,"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."}}