{"id":"W3175695364","doi":"10.3389/fnins.2021.646034","title":"Bundle-Specific Axon Diameter Index as a New Contrast to Differentiate White Matter Tracts","year":2021,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"EPSRC Centre for Doctoral Training in Medical Imaging; Centre d'Imagerie BioMédicale; Université de Lausanne; Université de Genève; Hôpitaux Universitaires de Genève; Ministero dell’Istruzione, dell’Università e della Ricerca; Engineering and Physical Sciences Research Council; École Polytechnique Fédérale de Lausanne; Centre Hospitalier Universitaire Vaudois; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Wolfson Foundation; Wellcome Trust; National Science Foundation","keywords":"White matter; Voxel; Axon; Diffusion MRI; Corpus callosum; Internal capsule; Tractography; Bundle; Spherical mean; Neuroscience; Magnetic resonance imaging; Anatomy; Computer science; Artificial intelligence; Biology; Mathematics; Materials science; Mathematical analysis; Medicine; Radiology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0000553271,0.0001638359,0.0002562012,0.0001820256,0.00007285588,0.00007537397,0.0002281792,0.00004465639,0.00007017449],"category_scores_gemma":[0.0001276176,0.000158352,0.00006282485,0.0007834859,0.0001037034,0.0001482123,0.0001059489,0.0002842646,0.0000370177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000577159,"about_ca_system_score_gemma":0.0001032206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006142652,"about_ca_topic_score_gemma":0.000002194324,"domain_scores_codex":[0.9983996,0.000029524,0.0002410096,0.0006778165,0.0002683977,0.0003836216],"domain_scores_gemma":[0.9989927,0.00002029693,0.00005522999,0.0005325761,0.00004117362,0.0003579926],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001000991,0.0004458454,0.7425908,0.00002263742,0.00000244608,0.0002460223,0.0002128707,0.00006893418,0.0881156,0.0002433061,0.1594765,0.008474942],"study_design_scores_gemma":[0.0007439213,0.0001546351,0.8091641,0.0001024319,0.0000125102,0.0001735361,0.00004369632,0.0007045803,0.01411453,0.001999494,0.1725193,0.0002672788],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2046904,0.0001268849,0.7759373,0.01550685,0.000923785,0.0005997533,0.00001049391,0.0001398652,0.002064766],"genre_scores_gemma":[0.92053,0.0001422788,0.05151248,0.02046061,0.00008332304,0.00006123633,0.000004989588,0.00003711142,0.007167943],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7244248,"threshold_uncertainty_score":0.6457407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04516596557874247,"score_gpt":0.3122785943264132,"score_spread":0.2671126287476707,"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."}}