{"id":"W2054766524","doi":"10.4137/mri.s10692","title":"Diffusion Tensor Metric Measurements as a Function of Diffusion Time in the Rat Central Nervous System","year":2012,"lang":"en","type":"article","venue":"Magnetic Resonance Insights","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Grey matter; Diffusion MRI; White matter; Fractional anisotropy; Diffusion; Physics; Thermal diffusivity; Anisotropy; Nuclear magnetic resonance; Chemistry; Magnetic resonance imaging; Medicine; Thermodynamics; Optics","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":[0.0001676011,0.0001568211,0.0002503509,0.0001733666,0.00009001952,0.00001038982,0.0001472356,0.00006763275,0.00003875823],"category_scores_gemma":[0.00007396457,0.00009885984,0.00006933547,0.0006925337,0.00005933355,0.00008495954,0.00004622651,0.000176109,0.00004192791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009092205,"about_ca_system_score_gemma":0.00002225248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005039758,"about_ca_topic_score_gemma":0.000002499572,"domain_scores_codex":[0.9985304,0.0001017405,0.0003408337,0.0002286242,0.0004861287,0.0003122481],"domain_scores_gemma":[0.9991725,0.00007153046,0.0001181691,0.0004741922,0.00007766177,0.0000859357],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001042432,0.00319043,0.1810725,0.0005003904,0.00001539055,0.00006538403,0.00248831,0.0000148033,0.4171498,0.005739407,0.004872532,0.3838486],"study_design_scores_gemma":[0.001086179,0.0005335888,0.926764,0.0003034179,0.0000848006,0.00008279793,0.000122289,0.0008906465,0.003350694,0.0002169685,0.06641576,0.0001488407],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9868079,0.00668199,0.0006000134,0.0003142605,0.0001216091,0.001096959,0.000002004163,0.000100023,0.004275285],"genre_scores_gemma":[0.9976802,0.0001738267,0.000853473,0.0002703023,0.0001119206,0.0001142507,0.000009281583,0.00002027598,0.0007664828],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7456915,"threshold_uncertainty_score":0.4031387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04734002903679904,"score_gpt":0.2858887376946053,"score_spread":0.2385487086578063,"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."}}