{"id":"W4317377578","doi":"10.1088/1361-6560/acb482","title":"<i>In vivo</i> estimation of anisotropic mechanical properties of the gastrocnemius during functional loading with MR elastography","year":2023,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Elasticity and Material Modeling","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Division of Chemical, Bioengineering, Environmental, and Transport Systems; National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health; National Science Foundation","keywords":"Elastography; Magnetic resonance elastography; Algorithm; Materials science; Anisotropy; Artificial intelligence; Computer science; Physics; Ultrasound; Acoustics","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":[0.00005213035,0.00005268238,0.0001359421,0.00005485733,0.00001411693,7.678425e-7,0.00003285331,0.00002780932,0.000006832446],"category_scores_gemma":[0.00001552901,0.00003153706,0.000009935712,0.0001984496,0.00008069791,0.00002975607,0.00001968048,0.000068146,1.973255e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005831103,"about_ca_system_score_gemma":0.000004784175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002400888,"about_ca_topic_score_gemma":0.00001692945,"domain_scores_codex":[0.9996647,0.00001335117,0.0001328446,0.00006365257,0.00003834333,0.00008714913],"domain_scores_gemma":[0.9998817,0.00003127726,0.00002363826,0.00004330489,0.00001142944,0.000008599867],"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":[0.00003220141,0.000007126571,0.0009745961,0.000173688,0.000008821774,3.111558e-7,0.0001750471,0.07933725,0.9175177,0.001640583,0.00001363436,0.000119007],"study_design_scores_gemma":[0.002129953,0.0004024219,0.006566234,0.001885801,0.00004269366,0.0000114454,0.0006087949,0.212066,0.7652653,0.01079299,0.00003427647,0.0001940096],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950666,0.00003569361,0.00464098,0.00004728068,0.0001110442,0.00005082573,0.000004108787,0.00001448347,0.00002898411],"genre_scores_gemma":[0.9997249,0.00004226544,0.0001486256,0.00001038606,0.00005756453,0.000007686482,0.000002400111,0.000004403805,0.000001728897],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1522524,"threshold_uncertainty_score":0.1286044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0637038345167915,"score_gpt":0.2554791684171949,"score_spread":0.1917753339004034,"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."}}