{"id":"W2152700820","doi":"10.7202/013257ar","title":"Use of Extralinguistic Knowledge in Translation","year":2006,"lang":"en","type":"article","venue":"Meta Journal des traducteurs","topic":"Interpreting and Communication in Healthcare","field":"Health Professions","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Competence (human resources); Inference; Computer science; Comprehension; Linguistics; Natural language processing; Source text; Psychology; Knowledge base; Artificial intelligence; Social psychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01264946,0.0005188148,0.0005429591,0.002551864,0.0009508753,0.003270597,0.0007128385,0.0007810597,0.002002502],"category_scores_gemma":[0.07520462,0.0004224219,0.0004671559,0.00178912,0.003537558,0.004957529,0.002429859,0.001370167,0.0003908845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008258593,"about_ca_system_score_gemma":0.001532262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00102905,"about_ca_topic_score_gemma":0.001336559,"domain_scores_codex":[0.9681202,0.02345997,0.002052651,0.00146988,0.00426483,0.0006324445],"domain_scores_gemma":[0.8616391,0.1094504,0.01256889,0.008017889,0.007396809,0.0009269429],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0009959938,0.0005213403,0.07914409,0.00196428,0.000200789,0.004331841,0.4682078,0.001748544,0.04015367,0.007421509,0.0005139863,0.3947962],"study_design_scores_gemma":[0.0002301712,0.002531067,0.5445036,0.002498646,0.0008009529,0.0223485,0.2137206,0.02351559,0.07967897,0.06044261,0.04911955,0.0006097554],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9423392,0.001145942,0.04129233,0.0007622344,0.00003356804,0.0001579517,0.00006611304,0.0001160406,0.01408663],"genre_scores_gemma":[0.9904483,0.0003752352,0.008334994,0.00009217941,0.00001738794,0.00004248334,0.00004961901,0.00002968492,0.000610047],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01264946,"threshold_uncertainty_score":0.06689757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2450704718692057,"score_gpt":0.448673067783348,"score_spread":0.2036025959141422,"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."}}