{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005776951,0.001072071,0.0005304198,0.0007646555,0.0002761629,0.0007242792,0.001110526,0.001069443,0.002062266],"category_scores_gemma":[0.001319287,0.0004205403,0.000943155,0.0005786675,0.0005007617,0.001660722,0.0009203996,0.0008426098,0.001206442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004523389,"about_ca_system_score_gemma":0.0005584229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001041208,"about_ca_topic_score_gemma":0.0009458701,"domain_scores_codex":[0.9997151,0.00005738034,0.00001216046,0.00005754189,0.0001360188,0.00002173405],"domain_scores_gemma":[0.9995487,0.0001858721,0.00004587702,0.00008555603,0.0001076913,0.00002622006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001904753,0.0001319944,0.0005726881,0.0002520972,0.0001022245,0.0003889084,0.0001272251,0.5425591,0.1748494,0.05966765,0.003063191,0.2180952],"study_design_scores_gemma":[0.000008728757,0.00001985731,0.00005424972,0.000004753824,0.000008130984,0.0001075103,0.000005441566,0.9718269,0.01688006,0.008618225,0.002455462,0.00001075609],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001933351,0.0000665443,0.9967379,0.0000419895,0.00001311525,0.0000147998,0.00002282501,0.0005396307,0.0006297435],"genre_scores_gemma":[0.1133272,0.0004451471,0.8828456,0.00009224617,0.00004607602,0.0001597619,0.0001840422,0.0003524841,0.002547486],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002062266,"threshold_uncertainty_score":0.00689894,"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."}}