{"id":"W4415323006","doi":"10.1002/mrm.70135","title":"A Flexible Approach for Fat‐Water Separation With Bipolar Readouts and Correction of Gradient‐Induced Phase and Amplitude Effects","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Body Composition Measurement Techniques","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada","keywords":"Amplitude; Separation (statistics); Phase (matter); Current (fluid); Separation method; Magnetic separation","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":[0.0004464846,0.0001492213,0.0004007768,0.000306434,0.00004444905,0.00000787651,0.00004001762,0.00007696076,0.00000594698],"category_scores_gemma":[0.0001051447,0.00009997057,0.00001592037,0.000265931,0.0001682472,0.0000517995,0.00001704188,0.0001303195,1.208416e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004728985,"about_ca_system_score_gemma":0.00002319026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001049124,"about_ca_topic_score_gemma":0.00001456715,"domain_scores_codex":[0.9989326,0.00005643369,0.000303135,0.0003087252,0.0002193844,0.0001797419],"domain_scores_gemma":[0.9994692,0.00009284606,0.00005619546,0.0001988635,0.000127543,0.00005537344],"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":[0.00295509,0.0004741886,0.02446901,0.001607308,0.00002534559,0.000009882472,0.001200696,0.00000324524,0.7588118,0.0003082054,0.001715233,0.20842],"study_design_scores_gemma":[0.03742468,0.02304047,0.1450854,0.006588804,0.0006049054,0.0001051781,0.000405038,0.01804236,0.7499359,0.0008165984,0.01753284,0.0004178217],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.953514,0.009650642,0.03228665,0.0007675385,0.0001151384,0.002519915,0.000002182725,0.00007928132,0.001064624],"genre_scores_gemma":[0.9911509,0.0002173509,0.007508417,0.0002525275,0.00005121407,0.000296236,0.00004323944,0.00001329342,0.0004668907],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2080021,"threshold_uncertainty_score":0.4076681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02363129849565347,"score_gpt":0.3292933291414865,"score_spread":0.305662030645833,"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."}}