{"id":"W1998153192","doi":"10.1016/j.jneumeth.2014.04.019","title":"White and gray matter contrast enhancement in MR images of the mouse brain in vivo using IR UTE with a cryo-coil at 9.4 T","year":2014,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Thunder Bay Regional Research Institute","funders":"","keywords":"Electromagnetic coil; Nuclear magnetic resonance; White matter; Echo time; Pulse sequence; Physics; Contrast-to-noise ratio; Nuclear medicine; Materials science; Magnetic resonance imaging; Image quality; Medicine; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004266074,0.000364275,0.00012629,0.0005040625,0.0001610636,0.0002679085,0.000252499,0.0005737268,0.002417102],"category_scores_gemma":[0.0002884824,0.0002622543,0.0001664931,0.000249494,0.0003797788,0.0004344159,0.0001985474,0.0005538712,0.0002606639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009647437,"about_ca_system_score_gemma":0.0001577843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007883421,"about_ca_topic_score_gemma":0.0007213654,"domain_scores_codex":[0.9999446,0.00001422709,0.000004884826,0.00001232841,0.000009071562,0.0000148715],"domain_scores_gemma":[0.9998418,0.00004626579,0.00003777862,0.0000123381,0.00003140859,0.00003034075],"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":[0.0008538984,0.00004118454,0.0003113388,0.0001120155,0.00001869285,0.0001563041,0.00004982365,0.0003098696,0.9952011,0.0002705438,0.0002247297,0.002450275],"study_design_scores_gemma":[0.0001460304,0.001258344,0.02078147,0.00005793004,0.0001624315,0.00207091,0.00008431569,0.003396249,0.9681624,0.0003190126,0.003534057,0.00002694095],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9645646,0.002320814,0.02680132,0.0004638065,0.00005890711,0.00006969828,0.0005586811,0.0003324537,0.004829694],"genre_scores_gemma":[0.9629214,0.002269999,0.02662182,0.0002841807,0.00004156896,0.00009850156,0.0005854164,0.0001199014,0.007057195],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002417102,"threshold_uncertainty_score":0.008085966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02959290362275295,"score_gpt":0.3873713529123272,"score_spread":0.3577784492895742,"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."}}