{"id":"W2763784867","doi":"10.1002/mrm.26945","title":"Scan–rescan of axcaliber, macromolecular tissue volume, and g‐ratio in the spinal cord","year":2017,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute; Polytechnique Montréal","funders":"National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Réseau en Bio-Imagerie du Quebec; Canadian Institutes of Health Research; National Institutes of Health; Canada Research Chairs; National Institute of Biomedical Imaging and Bioengineering; Fonds de Recherche du Québec - Santé; Multiple Sclerosis Society of Canada; Canada Foundation for Innovation","keywords":"Intraclass correlation; Magnetic resonance imaging; White matter; Spinal cord; Repeatability; Artifact (error); Medicine; Nuclear medicine; Relaxometry; Partial volume; Radiology; Chemistry; Biology; Neuroscience; Spin echo","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":[0.0003499463,0.0001205792,0.0003124683,0.00008782408,0.00007644387,0.00001152381,0.000291992,0.00004380803,0.0000460425],"category_scores_gemma":[0.0003066915,0.00008478152,0.00001634143,0.0001541103,0.0006607575,0.00003964726,0.00006384714,0.0002428797,0.00000157631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001785216,"about_ca_system_score_gemma":0.00002768292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007212464,"about_ca_topic_score_gemma":0.0001083219,"domain_scores_codex":[0.9989241,0.00003859507,0.0003313792,0.0002649697,0.0002528555,0.0001881251],"domain_scores_gemma":[0.9989614,0.00003457094,0.0001208276,0.0007916253,0.00004124,0.00005035683],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004368242,0.0001809597,0.1474925,0.0001827105,0.000002253783,0.0004483951,0.0003575814,0.000001026127,0.02203647,0.004249487,0.004361813,0.82025],"study_design_scores_gemma":[0.001337613,0.001799746,0.9052255,0.0007508924,0.0000214434,0.0001427421,0.00007790677,0.0005349325,0.0009803452,0.002895741,0.08614465,0.00008846196],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9234653,0.01971581,0.001752325,0.04570143,0.00007008218,0.001436654,0.000007188286,0.0000368309,0.007814358],"genre_scores_gemma":[0.9935479,0.001396996,0.003393202,0.0008392997,0.00007510953,0.00008912706,0.000003325935,0.00001394245,0.0006411037],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8201615,"threshold_uncertainty_score":0.345729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0554028314702005,"score_gpt":0.389358564859911,"score_spread":0.3339557333897105,"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."}}