{"id":"W4403157986","doi":"10.1111/vru.13444","title":"Ultrasonographic assessment of equine metacarpal cartilage thickness is more accurate than computed tomographic arthrography","year":2024,"lang":"en","type":"article","venue":"Veterinary Radiology & Ultrasound","topic":"Veterinary Equine Medical Research","field":"Veterinary","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Fonds de Recherche du Québec - Santé","keywords":"Medicine; Sagittal plane; Computed tomographic; Osteochondrosis; Cartilage; Histology; Radiology; Ultrasonography; Anatomy; Nuclear medicine; Computed tomography; Pathology","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":[0.00175503,0.0003856812,0.0004482092,0.001334257,0.0001780023,0.0006374369,0.0002295945,0.0005335853,0.001378835],"category_scores_gemma":[0.008000613,0.0002815228,0.0002224755,0.0003763884,0.0004083897,0.000926342,0.0002276332,0.0002507805,0.0004916869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001701066,"about_ca_system_score_gemma":0.0001640252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001271811,"about_ca_topic_score_gemma":0.003290558,"domain_scores_codex":[0.9989918,0.0003410153,0.0001205497,0.0001718442,0.000321589,0.00005324633],"domain_scores_gemma":[0.9938951,0.002052078,0.002165947,0.0003035387,0.001412268,0.0001709962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004643079,0.00007814682,0.7481555,0.0003566337,0.0001870625,0.0007424532,0.0008123756,0.000732762,0.1630067,0.00007897002,0.0002329358,0.08515213],"study_design_scores_gemma":[0.000006965498,0.0005864044,0.9807396,0.00009648763,0.00008251883,0.002896692,0.0004304766,0.001188549,0.01257903,0.0000650991,0.001308894,0.00001934211],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9834216,0.005096163,0.008809803,0.0001171677,0.00004879402,0.00003105837,0.0001324179,0.0001208213,0.002222309],"genre_scores_gemma":[0.9920598,0.00104267,0.006242603,0.00003311253,0.00002953939,0.000009162734,0.00006897784,0.00001460817,0.0004993994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00175503,"threshold_uncertainty_score":0.009281576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0749636458683252,"score_gpt":0.4026672383618375,"score_spread":0.3277035924935123,"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."}}