{"id":"W4400387414","doi":"10.1111/vru.13405","title":"Ex vivo evaluation of the soft tissue components of the equine stifle using 3 Tesla magnetic resonance imaging under flexion, extension, and loading","year":2024,"lang":"en","type":"article","venue":"Veterinary Radiology & Ultrasound","topic":"Tendon Structure and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Cegep de Saint Hyacinthe","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Stifle joint; Medicine; Magnetic resonance imaging; Ligament; Cruciate ligament; Anatomy; Soft tissue; Medial collateral ligament; Anterior cruciate ligament; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000393019,0.0003627998,0.0001215785,0.0003021775,0.0002408561,0.000265139,0.0001360383,0.0003994187,0.002000923],"category_scores_gemma":[0.00041467,0.0002357527,0.0001196282,0.0001069747,0.000383363,0.000428814,0.0001547094,0.0002343659,0.000249089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009725924,"about_ca_system_score_gemma":0.0001352293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005231772,"about_ca_topic_score_gemma":0.001423013,"domain_scores_codex":[0.9999238,0.0000173813,0.00000712888,0.00001717832,0.00001853476,0.00001596829],"domain_scores_gemma":[0.9997674,0.00006368053,0.00004952558,0.00002399716,0.00006505398,0.0000303031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002087673,0.00005448586,0.001818518,0.00004899588,0.000007684415,0.0001860777,0.0001049107,0.0001258009,0.9943328,0.00002716553,0.00003028777,0.003054541],"study_design_scores_gemma":[0.00006794441,0.007565319,0.334641,0.00007721023,0.0001224704,0.008922392,0.0007721166,0.002847995,0.6402914,0.0001738727,0.004470001,0.00004822959],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952009,0.0003565718,0.00358288,0.00002579591,0.000005915515,0.00002603343,0.00008115637,0.00002303575,0.0006977055],"genre_scores_gemma":[0.9918671,0.0005439833,0.005629592,0.0000572164,0.00001280576,0.00004256165,0.0002315106,0.00001823069,0.001597003],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002000923,"threshold_uncertainty_score":0.00669378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05345706164412121,"score_gpt":0.3333158172303669,"score_spread":0.2798587555862456,"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."}}