{"id":"W2550930751","doi":"10.1016/j.jse.2016.09.038","title":"Optimizing the rehabilitation of elbow lateral collateral ligament injuries: a biomechanical study","year":2016,"lang":"en","type":"article","venue":"Journal of Shoulder and Elbow Surgery","topic":"Elbow and Forearm Trauma Treatment","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"St Joseph's Health Care; Western University","funders":"Physicians' Services Incorporated Foundation","keywords":"Elbow; Medicine; Forearm; Ligament; Range of motion; Medial collateral ligament; Valgus; Physical medicine and rehabilitation; Physical therapy; Orthodontics; Surgery","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001107544,0.0001540829,0.0005855892,0.0002393523,0.0000687989,0.00002290814,0.00005785868,0.00007057846,0.00004257861],"category_scores_gemma":[0.0001115809,0.00006926474,0.0002647791,0.0001592529,0.0001245059,0.0001639098,0.00003468348,0.0001286026,0.000001219843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007188182,"about_ca_system_score_gemma":0.0001059079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001270855,"about_ca_topic_score_gemma":0.000004097075,"domain_scores_codex":[0.9983185,0.0001075325,0.0008189003,0.0001433033,0.0004069365,0.0002048281],"domain_scores_gemma":[0.9983939,0.0007406974,0.0003256499,0.0001869814,0.0002100678,0.0001426973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004075606,0.002853401,0.87216,0.0002044506,0.001416093,0.0002391274,0.01057602,0.000006658462,0.03015111,0.00007433675,0.002619297,0.07562386],"study_design_scores_gemma":[0.01211946,0.0137778,0.9269454,0.003743964,0.0017492,0.001206288,0.008973293,0.00006059865,0.02553405,0.001709212,0.003619002,0.0005616887],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930253,0.0005995939,0.0001363277,0.005619701,0.0002616674,0.0002950453,0.00000481692,0.000008948974,0.00004861291],"genre_scores_gemma":[0.9987344,0.0003263813,0.0004923823,0.0001314592,0.0001515309,0.000008906341,6.112543e-7,0.00001565424,0.000138648],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07506217,"threshold_uncertainty_score":0.2824534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02717582055574006,"score_gpt":0.2987260152898738,"score_spread":0.2715501947341337,"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."}}