{"id":"W2516513989","doi":"10.5539/ells.v6n3p42","title":"Effect of Technological Developments on Ethical Position of Translator","year":2016,"lang":"en","type":"article","venue":"English Language and Literature Studies","topic":"Translation Studies and Practices","field":"Arts and Humanities","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Crowdsourcing; Position (finance); Translation (biology); Engineering ethics; Machine translation; Ethical issues; Computer science; Process (computing); Sociology; Knowledge management; Linguistics; Epistemology; Artificial intelligence; Business; Philosophy; Engineering; World Wide Web; Chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002865965,0.000110156,0.0002463926,0.00006023414,0.00009723895,0.00001854794,0.00004165311,0.00008910503,0.00004500285],"category_scores_gemma":[0.0001728115,0.00005252317,0.00004726448,0.00003953788,0.0003031096,0.00009973309,0.00001584884,0.0001528672,0.000001108308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003783413,"about_ca_system_score_gemma":0.000002771955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001620958,"about_ca_topic_score_gemma":0.00001160148,"domain_scores_codex":[0.9993939,0.0001002705,0.0001693996,0.0001260424,0.0001228134,0.0000875091],"domain_scores_gemma":[0.9990076,0.0007329996,0.0000691987,0.0000689747,0.0001064616,0.00001475095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006028024,0.00005749843,0.0004515864,0.000449937,0.0004534255,0.0000233496,0.6630257,6.984121e-8,0.002143604,0.1202187,0.0005439505,0.2120294],"study_design_scores_gemma":[0.005033822,0.004410274,0.0006408037,0.003849523,0.0003655445,0.00001005836,0.1088087,4.520269e-7,0.05431698,0.001156124,0.8207027,0.0007049941],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.961089,0.0198458,0.00000509263,0.0009551091,0.0001939851,0.0001373309,0.00009843706,0.0000522024,0.01762312],"genre_scores_gemma":[0.9987311,0.0008041456,0.00004703641,0.00006020488,0.0001212692,0.00001059937,0.00000383238,0.000004893992,0.0002169488],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8201588,"threshold_uncertainty_score":0.2141833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01204148482455489,"score_gpt":0.2832188003728396,"score_spread":0.2711773155482847,"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."}}