{"id":"W2055456625","doi":"10.1016/j.jmr.2011.12.019","title":"Local T2 distribution measurements with DANTE-Z slice selection","year":2012,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance","topic":"NMR spectroscopy and applications","field":"Physics and Astronomy","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sinc function; Pulse sequence; Wafer; Position (finance); Relaxation (psychology); Sequence (biology); Selection (genetic algorithm); Resolution (logic); Analytical Chemistry (journal); Pulse (music); Sample (material); Selection principle; Distribution (mathematics); Nuclear magnetic resonance; Chemistry; Materials science; Computational physics; Mathematics; Physics; Optics; Mathematical analysis; Computer science; Chromatography","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":[0.0002022284,0.00008270923,0.0001139036,0.00001885653,0.00008921477,0.0000208385,0.00009613312,0.00001764479,0.0002133174],"category_scores_gemma":[0.000003399705,0.00006312242,0.00004471221,0.0001619262,0.00003924209,0.0001956117,0.000008710826,0.0001618141,0.0000186059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004836323,"about_ca_system_score_gemma":0.00004762481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002493381,"about_ca_topic_score_gemma":0.000002165767,"domain_scores_codex":[0.9992532,0.00002994452,0.0002095102,0.00006731235,0.0002432349,0.0001968664],"domain_scores_gemma":[0.999481,0.00001673704,0.000194263,0.00008171426,0.0001367938,0.00008949774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003888897,0.00127909,0.6459435,0.000020469,0.00007802637,0.000001606651,0.0003223305,0.000196148,0.02418595,0.02266919,0.01842976,0.2864851],"study_design_scores_gemma":[0.001764127,0.0008498356,0.571486,0.0001454164,0.0001444294,0.00007662697,0.0002767034,0.0003675847,0.05740676,0.001087822,0.366088,0.0003066809],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5953239,0.003044656,0.3947944,0.0003827745,0.0001646172,0.0001859362,0.00001990199,0.00001187095,0.006071925],"genre_scores_gemma":[0.997588,0.00001186894,0.001592553,0.00002015404,0.0004176912,0.00000802036,0.000003946532,0.000007076094,0.0003506508],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4022641,"threshold_uncertainty_score":0.2574058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01230588437762642,"score_gpt":0.2873837572923073,"score_spread":0.2750778729146808,"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."}}