{"id":"W2008655880","doi":"10.1016/j.mri.2008.01.047","title":"Is diffusion anisotropy an accurate monitor of myelination?","year":2008,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":229,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary; University of British Columbia Hospital","funders":"Killam Trusts; Bundesministerium für Bildung und Forschung","keywords":"Fractional anisotropy; Anisotropy; Diffusion MRI; White matter; Myelin; Thermal diffusivity; Nuclear magnetic resonance; Chemistry; Diffusion; Materials science; Physics; Neuroscience; Psychology; Thermodynamics; Optics; Magnetic resonance imaging; Medicine","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":[0.006520154,0.0007370639,0.002151365,0.001802115,0.0004138537,0.002321474,0.001241378,0.003323772,0.001052691],"category_scores_gemma":[0.02672859,0.0006120384,0.000361332,0.001818643,0.003499896,0.005831316,0.0004546521,0.001689574,0.00131279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005766769,"about_ca_system_score_gemma":0.0005800137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001809613,"about_ca_topic_score_gemma":0.001391701,"domain_scores_codex":[0.9974814,0.000790915,0.0003656388,0.0004638694,0.000783574,0.0001146042],"domain_scores_gemma":[0.9897262,0.004817028,0.001861557,0.001119259,0.002142407,0.0003335178],"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":[0.001713524,0.0002363623,0.1987254,0.00278928,0.001439863,0.001723554,0.0006669776,0.002873078,0.06870767,0.0363237,0.04497791,0.6398227],"study_design_scores_gemma":[0.0002195988,0.001232009,0.3334341,0.00281592,0.001986077,0.03670578,0.002243942,0.02817677,0.1650053,0.2065623,0.2207814,0.0008368215],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.238387,0.4660694,0.1614971,0.09791654,0.01147546,0.00008293708,0.001476667,0.001443853,0.02165108],"genre_scores_gemma":[0.8207929,0.1226096,0.03570773,0.007491529,0.008501105,0.00007631843,0.0003488114,0.0002645353,0.004207443],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006520154,"threshold_uncertainty_score":0.0344823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05355865973126047,"score_gpt":0.3531368512188817,"score_spread":0.2995781914876212,"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."}}