{"id":"W4409364119","doi":"10.26641/2307-0404.2025.1.325375","title":"Translation, cross-cultural adaptation and content validation of the Canadian Occupational Performance Measure (COPM) in the Ukrainian language","year":2025,"lang":"en","type":"article","venue":"Medicni perspektivi","topic":"Ergonomics and Human Factors","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ukrainian; Adaptation (eye); Measure (data warehouse); Translation (biology); Content (measure theory); Linguistics; Psychology; Computer science; Natural language processing; Biology; Neuroscience; Mathematics; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002486629,0.0000618894,0.00006292362,0.00006559043,0.0001020707,0.00004022668,0.00009640094,0.00004255032,0.00002131105],"category_scores_gemma":[0.00003545953,0.00003993146,0.00002245109,0.0001081071,0.00007984766,0.0001105773,0.000003458049,0.0001053174,9.146397e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009410789,"about_ca_system_score_gemma":0.00008988346,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.007492517,"about_ca_topic_score_gemma":0.1313342,"domain_scores_codex":[0.9995667,0.00002363057,0.0001315664,0.00006723242,0.0001187801,0.00009210469],"domain_scores_gemma":[0.9997858,0.00003343173,0.00001966763,0.00008570321,0.00005433185,0.00002108156],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00004287651,0.00003240057,0.4361557,0.0002130451,0.0001112978,0.000001608881,0.4924327,0.02225268,0.002794799,0.003984983,0.0005568735,0.04142102],"study_design_scores_gemma":[0.0004121317,0.000008551016,0.9756494,0.00005928141,0.00001300007,9.661667e-7,0.004957708,0.01586666,0.000906647,0.00001693848,0.002036892,0.000071783],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956762,0.0003458542,0.00002221922,0.0005230564,0.0001600445,0.0001434876,0.0000179945,0.000009115412,0.003102084],"genre_scores_gemma":[0.999777,0.00001419127,0.00002569275,0.00007893568,0.00002720477,0.000009884167,0.0000178111,0.000003726428,0.00004556192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5394937,"threshold_uncertainty_score":0.9991167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04738745142014732,"score_gpt":0.265158569316617,"score_spread":0.2177711178964697,"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."}}