{"id":"W2054335197","doi":"10.1002/mrm.22487","title":"Transverse relaxometry with stimulated echo compensation","year":2010,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":185,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Heritage Foundation for Medical Research; Fondation pour la Recherche Médicale","keywords":"Multislice; Relaxometry; Spin echo; Nuclear magnetic resonance; Pulse sequence; SIGNAL (programming language); Physics; Coherence (philosophical gambling strategy); Adiabatic process; Transverse plane; Computer science; Magnetic resonance imaging; Medicine; Radiology","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":[0.0002004815,0.0001498651,0.0003071172,0.0001830137,0.00004330484,0.000003497323,0.00009792425,0.0001115971,0.0007875829],"category_scores_gemma":[0.00009999564,0.0001074121,0.00002176614,0.0007139302,0.0002909345,0.00004733193,0.00001017882,0.00054888,0.00001598599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003205581,"about_ca_system_score_gemma":0.00003992959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008936371,"about_ca_topic_score_gemma":0.0001090592,"domain_scores_codex":[0.998874,0.00001338198,0.0003046418,0.0002926841,0.0002914281,0.0002238838],"domain_scores_gemma":[0.9992151,0.00008561886,0.00005694884,0.0004338902,0.00009294706,0.0001154724],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001326154,0.0007004076,0.09124833,0.0001480062,0.000007520568,0.0004157971,0.001364384,0.0002690522,0.2422321,0.007713174,0.004153697,0.6504214],"study_design_scores_gemma":[0.01182608,0.003649317,0.6332154,0.001088846,0.0001157567,0.0004147106,0.0004792398,0.01182158,0.0052064,0.002767346,0.3289378,0.0004775508],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9422396,0.001724135,0.0243048,0.009352883,0.0001207741,0.001606704,0.000005788737,0.0002918511,0.02035348],"genre_scores_gemma":[0.9455385,0.0002967003,0.05208594,0.0005668494,0.0001192819,0.00009317158,0.00002698751,0.00002660427,0.001246006],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6499438,"threshold_uncertainty_score":0.862348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01449246453366811,"score_gpt":0.3063822027070628,"score_spread":0.2918897381733947,"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."}}