{"id":"W6946061051","doi":"10.26226/morressier.5cb58cfec668520010b56e0a","title":"IMAGING MARKER FOR COGNITIVE IMPAIRMENT DUE TO CEREBRAL WHITE MATTER LESIONS BASED ON SKELETONIZATION OF WHITE MATTER TRACTS AND DIFFUSION HISTOGRAMS","year":2017,"lang":"en","type":"other","venue":"BiblioBoard Library Catalog (Open Research Library)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hyperintensity; Cognition; White matter; Neuropsychology; Diffusion MRI; Skeletonization; Montreal Cognitive Assessment; Cognitive impairment; Cognitive decline; Magnetic resonance imaging","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","bibliometrics","scholarly_communication","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.001214895,0.001433497,0.001764521,0.02336104,0.00115116,0.00368695,0.003871469,0.0007456068,0.0284717],"category_scores_gemma":[0.0001871797,0.001318172,0.0004392636,0.006503591,0.001072988,0.008555501,0.006212581,0.001305445,0.004145399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001237166,"about_ca_system_score_gemma":0.001169767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004685044,"about_ca_topic_score_gemma":0.00006008297,"domain_scores_codex":[0.9903308,0.001533656,0.001120866,0.00275605,0.002031501,0.002227142],"domain_scores_gemma":[0.9935572,0.000836172,0.001108549,0.002790494,0.0002390404,0.001468565],"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":[0.002490166,0.0007591,0.2841451,0.000873337,0.0001133953,0.00013153,0.0001304121,0.0000034943,0.00006654942,0.00005439615,0.710107,0.00112553],"study_design_scores_gemma":[0.004386182,0.0007280285,0.4137439,0.005485025,0.0001086555,0.00002156365,0.00008421148,0.0004475738,0.0004153559,0.0002115343,0.5729643,0.001403736],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.006974861,0.0009816113,0.0009702033,0.02362996,0.0006324931,0.02290584,0.032019,0.0009346587,0.9109514],"genre_scores_gemma":[0.02409255,0.0002247181,0.01483007,0.006216256,0.0007582948,0.002905555,0.03120084,0.006070117,0.9137016],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1371428,"threshold_uncertainty_score":0.9998415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03677705516148452,"score_gpt":0.3222601217945371,"score_spread":0.2854830666330526,"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."}}