{"id":"W1513182332","doi":"10.1002/mrm.25510","title":"Multivendor implementation and comparison of volumetric whole‐brain echo‐planar MR spectroscopic imaging","year":2014,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health","keywords":"Echo-planar imaging; Nuclear magnetic resonance; Echo (communications protocol); Magnetic resonance imaging; Neuroimaging; Nuclear medicine; Materials science; Physics; Computer science; Medicine; Radiology","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":[0.0003245682,0.0001329847,0.0004315468,0.0002716789,0.00003827337,0.000003592608,0.000078688,0.0000365776,0.0001248318],"category_scores_gemma":[0.0002121429,0.0001140567,0.0000209677,0.0004975366,0.0002048355,0.00004164503,0.00002344717,0.0001778622,0.000003688267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004962327,"about_ca_system_score_gemma":0.00001723473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002664879,"about_ca_topic_score_gemma":0.00006056999,"domain_scores_codex":[0.9987545,0.0000406962,0.0004755236,0.00027785,0.0002316843,0.0002197282],"domain_scores_gemma":[0.9992675,0.0001961625,0.0001395748,0.0002605757,0.00005824637,0.00007790461],"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":[0.00004233489,0.00008551319,0.3758629,0.00008074571,0.000001279122,0.000004434633,0.0004770805,0.000002373895,0.0472227,0.0009089105,0.004335617,0.5709761],"study_design_scores_gemma":[0.005078942,0.001583452,0.8519987,0.0005534067,0.00005314644,0.00001984436,0.001760646,0.01085196,0.008507082,0.002041372,0.1173789,0.0001725598],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8292585,0.02604663,0.1112686,0.02700999,0.000105434,0.002176021,0.00001727113,0.0001399734,0.003977598],"genre_scores_gemma":[0.9644995,0.0002848409,0.03405201,0.0005102353,0.0001032742,0.00007912915,0.00003364365,0.00001729838,0.0004200854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5708035,"threshold_uncertainty_score":0.4651095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01886247297123826,"score_gpt":0.3795907349979817,"score_spread":0.3607282620267435,"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."}}