{"id":"W4400642964","doi":"10.1162/imag_a_00247","title":"Uncovering patterns of white matter degeneration in normal aging: Links between morphometry and microstructure","year":2024,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Degeneration (medical); Psychology; Biology; Pathology; Medicine; Magnetic resonance imaging","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008497992,0.0001016366,0.0001274353,0.0002299004,0.00006578743,0.0000537202,0.0000905369,0.0000274978,0.000006842705],"category_scores_gemma":[0.00002008007,0.00009526483,0.00002545214,0.000414835,0.00009409888,0.0002352591,0.0001224605,0.0003207735,0.000001221095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002163282,"about_ca_system_score_gemma":0.00002545513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001727455,"about_ca_topic_score_gemma":9.218065e-7,"domain_scores_codex":[0.9991375,0.00001093152,0.0001915017,0.0003555561,0.0001322552,0.0001722238],"domain_scores_gemma":[0.9996702,0.00002860164,0.00003701606,0.0001915086,0.00002073786,0.00005193521],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000001131325,0.000004958903,0.7438418,0.00007438498,2.719772e-7,0.00002033716,0.00007328775,0.00005027949,0.2544296,0.00001958197,0.00005305817,0.001431324],"study_design_scores_gemma":[0.0001139354,0.00001754312,0.9291894,0.0001931668,0.00001206807,0.0001736464,0.000009151383,0.002950124,0.06508406,0.0001953141,0.001964593,0.00009697095],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9616297,0.0001395536,0.03493833,0.002865625,0.00009648961,0.0001443992,0.00002633585,0.00008865052,0.00007085477],"genre_scores_gemma":[0.9953285,0.0000370178,0.003365915,0.001070619,0.00005254779,0.000007565799,0.000005696339,0.0000178783,0.0001142043],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1893455,"threshold_uncertainty_score":0.3884787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02655240432414101,"score_gpt":0.3235926997866115,"score_spread":0.2970402954624705,"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."}}