{"id":"W2116266958","doi":"10.1002/jmri.20210","title":"Muscle kinematics during isometric contraction: Development of phase contrast and spin tag techniques to study healthy and atrophied muscles","year":2004,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canmore Museum and Geoscience Centre","funders":"","keywords":"Isometric exercise; Biomedical engineering; Repeatability; Contraction (grammar); Kinematics; Nuclear medicine; Scanner; Medicine; Anatomy; Computer science; Physics; Mathematics; Artificial intelligence; Internal medicine","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":[0.0003199777,0.0001282408,0.0003851124,0.000350347,0.000106866,0.00001889522,0.00006535013,0.00002417332,0.000005677842],"category_scores_gemma":[0.0001129831,0.0001104499,0.0000329683,0.0003490583,0.00006357022,0.0001115474,0.00003993591,0.0001835204,2.359651e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008436967,"about_ca_system_score_gemma":0.00008648981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000818443,"about_ca_topic_score_gemma":0.00000253078,"domain_scores_codex":[0.998678,0.00001561094,0.0007283528,0.0001538425,0.0002541459,0.0001700659],"domain_scores_gemma":[0.999069,0.00004511554,0.0003580934,0.0001378954,0.0002279175,0.0001619754],"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":[0.0003146577,0.0009758418,0.002488596,0.00009940389,0.000007961268,0.00008291937,0.0009241572,0.000007735463,0.1301393,0.00005697969,0.00001836623,0.8648841],"study_design_scores_gemma":[0.01737935,0.005060697,0.8785025,0.001390699,0.0002100089,0.001611613,0.003505533,0.0001165179,0.08252354,0.0008331941,0.008467534,0.0003988363],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9484515,0.007515302,0.04152866,0.001676399,0.00001857581,0.0007430656,0.000002176591,0.00002487199,0.00003942166],"genre_scores_gemma":[0.7246121,0.0006758748,0.2744981,0.000121383,0.00005210964,0.00002130192,2.378411e-7,0.00001230278,0.000006625834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8760139,"threshold_uncertainty_score":0.4504018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01622583824641909,"score_gpt":0.3409073980135964,"score_spread":0.3246815597671773,"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."}}