{"id":"W2008221065","doi":"10.1002/mrm.10250","title":"Orientational diffusion reflects fiber structure within a voxel","year":2002,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; University of Toronto","funders":"Canada Research Chairs","keywords":"Diffusion; Voxel; Diffusion MRI; Fiber; Orientation (vector space); Effective diffusion coefficient; Fiber bundle; Nuclear magnetic resonance; Materials science; Geometry; Physics; Mathematics; Magnetic resonance imaging; Computer science; Artificial intelligence","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":[0.0005341251,0.0003527615,0.0003070573,0.001410263,0.0002597547,0.000694371,0.0003326201,0.0004427673,0.001579011],"category_scores_gemma":[0.001914266,0.0002838033,0.0002708051,0.0008683475,0.000729292,0.001449768,0.0004496428,0.0003823515,0.0004763449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004636967,"about_ca_system_score_gemma":0.0004556112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002050235,"about_ca_topic_score_gemma":0.002534244,"domain_scores_codex":[0.9997818,0.00003568355,0.00001038229,0.00007865882,0.00007574074,0.00001788019],"domain_scores_gemma":[0.9991978,0.0003038061,0.000216315,0.0001023007,0.0001414678,0.00003835962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003363867,0.0001076375,0.03547071,0.0005242304,0.0002525008,0.0002584136,0.0007072458,0.04420885,0.7225217,0.03005133,0.000923318,0.1646375],"study_design_scores_gemma":[0.00006709115,0.0008058938,0.1375899,0.0001114769,0.0003422299,0.003409106,0.0005934894,0.3970405,0.3736671,0.06730861,0.01864058,0.0004240297],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.431987,0.0016333,0.5573502,0.0003094773,0.00005796817,0.00006497689,0.0004046473,0.0007112857,0.007481277],"genre_scores_gemma":[0.8905381,0.001388032,0.1061464,0.0000439435,0.00002682855,0.00002128898,0.0001826074,0.0001156437,0.001537092],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002050235,"threshold_uncertainty_score":0.005282342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05733470017587754,"score_gpt":0.3509653606095507,"score_spread":0.2936306604336732,"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."}}