{"id":"W4233741447","doi":"10.1002/mrm.1167","title":"Chemical shift imaging with spectrum modeling","year":2001,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Nuclear magnetic resonance; Imaging phantom; Amplitude; Chemical shift; Spin echo; Nuclear magnetic resonance spectroscopy; Nonlinear system; Materials science; Magnetic resonance imaging; Physics; Chemistry; Computational physics; Optics","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":[0.0001433294,0.0001613586,0.0003155525,0.0001113924,0.00003338165,0.000004481692,0.0001118311,0.00004407587,0.0002865275],"category_scores_gemma":[0.00004759189,0.0001166646,0.00002325572,0.0004646791,0.0001799618,0.000045831,0.00002821239,0.0002946975,0.00001000434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007048018,"about_ca_system_score_gemma":0.00003393734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000151581,"about_ca_topic_score_gemma":0.00002523082,"domain_scores_codex":[0.9987321,0.000008609324,0.0003023082,0.0003439157,0.0002761915,0.0003368451],"domain_scores_gemma":[0.9993907,0.00003463489,0.00003765974,0.0003863103,0.00003260544,0.0001180473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001732751,0.0007546827,0.1964051,0.0001563332,0.00000698292,0.002546713,0.001473548,0.001337043,0.02714478,0.01270044,0.003515741,0.7522259],"study_design_scores_gemma":[0.01819355,0.002317729,0.08324002,0.006035469,0.0002367764,0.003648817,0.001326642,0.5056171,0.004019493,0.04980942,0.3241035,0.00145152],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6364197,0.02207434,0.2254576,0.07455546,0.00006256266,0.00146257,0.000002440754,0.0004339249,0.03953146],"genre_scores_gemma":[0.9704711,0.00119722,0.02612765,0.001243518,0.0002630078,0.000115581,0.00001043153,0.00003195866,0.0005395369],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7507744,"threshold_uncertainty_score":0.4757444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01589557974093214,"score_gpt":0.2998084529958994,"score_spread":0.2839128732549672,"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."}}