{"id":"W3106889884","doi":"10.1051/sicotj/2020042","title":"Cross-cultural adaptation and translation of the Constant Murley Score into Arabic","year":2020,"lang":"en","type":"article","venue":"SICOT-J","topic":"Shoulder Injury and Treatment","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Arabic; Adaptation (eye); Translation (biology); Constant (computer programming); Medicine; Psychology; Computer science; Linguistics; Philosophy; Biology; Neuroscience","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003887956,0.0006389667,0.0002902643,0.001010622,0.0008477968,0.0008670164,0.0004062724,0.0002498738,0.003339483],"category_scores_gemma":[0.01116902,0.0001951442,0.0003967143,0.001030365,0.0005618074,0.0005279578,0.001027069,0.0005864017,0.001004901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005491718,"about_ca_system_score_gemma":0.001405864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003268255,"about_ca_topic_score_gemma":0.004088412,"domain_scores_codex":[0.9970939,0.001369699,0.000440181,0.0002489882,0.0007361987,0.00011102],"domain_scores_gemma":[0.9958676,0.000973484,0.0004413424,0.0003305617,0.002267018,0.0001199142],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007920247,0.001038802,0.2603007,0.001811186,0.0002232592,0.0030048,0.04195451,0.001443917,0.02068392,0.003580681,0.01135803,0.6538082],"study_design_scores_gemma":[0.0002779044,0.002832566,0.78133,0.003382263,0.000434867,0.009881485,0.03289635,0.004504283,0.02170633,0.005504687,0.136912,0.0003373055],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9609479,0.002312282,0.01203833,0.001311462,0.0006351533,0.00154538,0.0009866237,0.0001145943,0.02010839],"genre_scores_gemma":[0.9363757,0.003446786,0.05341524,0.0005558791,0.0001272902,0.001430326,0.0009266706,0.00008500239,0.003637134],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.003887956,"threshold_uncertainty_score":0.0205617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0776275819674843,"score_gpt":0.3352641823211429,"score_spread":0.2576366003536586,"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."}}