{"id":"W1970150526","doi":"10.1186/1471-2342-13-30","title":"Quantification of cervical spine muscle fat: a comparison between T1-weighted and multi-echo gradient echo imaging using a variable projection algorithm (VARPRO)","year":2013,"lang":"en","type":"article","venue":"BMC Medical Imaging","topic":"Musculoskeletal pain and rehabilitation","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Center for Advancing Translational Sciences; National Institutes of Health; Northwestern University","keywords":"Medicine; Magnetic resonance imaging; Whiplash; Neck pain; Nuclear medicine; Gradient echo; Concordance; Cervical vertebrae; Cervical spine; Algorithm; Radiology; Anatomy; Mathematics; Pathology; Surgery","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":[0.004146962,0.0005500066,0.0003497142,0.001618382,0.0002634003,0.001037594,0.0005759005,0.0007063339,0.001058861],"category_scores_gemma":[0.006602779,0.00034097,0.0003635757,0.0007969342,0.0003962343,0.0006717866,0.0005753855,0.0003484943,0.0003394751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002144514,"about_ca_system_score_gemma":0.0004447066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008152284,"about_ca_topic_score_gemma":0.00115338,"domain_scores_codex":[0.9989492,0.000448865,0.0001065174,0.0002419423,0.0002145007,0.00003911127],"domain_scores_gemma":[0.9981639,0.000873015,0.0002955367,0.0001762182,0.0004103461,0.00008096299],"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":[0.006495657,0.0003793383,0.1387071,0.001831878,0.001130204,0.0004099028,0.001437737,0.0156996,0.3663311,0.002237301,0.001083107,0.464257],"study_design_scores_gemma":[0.0004272727,0.004869968,0.590103,0.0003153689,0.001082906,0.006588331,0.0009773087,0.2499335,0.1355642,0.002839985,0.007014439,0.0002836203],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7665253,0.002084485,0.228297,0.0001034809,0.00004910628,0.000335901,0.0003012928,0.0008831459,0.001420327],"genre_scores_gemma":[0.6884956,0.0004929057,0.3096199,0.00003775001,0.00001244926,0.000292333,0.0002944757,0.0002120717,0.0005425133],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.004146962,"threshold_uncertainty_score":0.02193153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0313438287860976,"score_gpt":0.3305998333476247,"score_spread":0.2992560045615271,"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."}}