{"id":"W4244269507","doi":"10.7202/1021222ar","title":"Rethinking Transediting","year":2013,"lang":"en","type":"article","venue":"Meta Journal des traducteurs","topic":"Translation Studies and Practices","field":"Arts and Humanities","cited_by":152,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coining (mint); Term (time); Computer science; Translation (biology); Dynamic and formal equivalence; Linguistics; Focus (optics); Source text; Context (archaeology); Translation studies; Explanatory power; Natural language processing; Epistemology; Artificial intelligence; History; Machine translation; Philosophy","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004571486,0.0001393245,0.0002309752,0.00007712768,0.001069326,0.000849047,0.000144282,0.00002262605,0.01064186],"category_scores_gemma":[0.00002315164,0.00009566564,0.0002392574,0.00003972123,0.0002132779,0.001439457,0.000005350845,0.0003636556,0.0001515628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001040333,"about_ca_system_score_gemma":0.0000127651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001345093,"about_ca_topic_score_gemma":0.0001858611,"domain_scores_codex":[0.9989405,0.0001294684,0.0003189879,0.0001174539,0.0002416869,0.0002519391],"domain_scores_gemma":[0.9993201,0.00019684,0.0001538765,0.00008271368,0.000155841,0.00009056726],"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":[0.00001768261,0.00006615944,0.0002182056,0.00005099683,0.001863652,0.00001939928,0.0529459,0.00002846569,0.0004225611,0.06364745,0.008367365,0.8723522],"study_design_scores_gemma":[0.0001852956,0.00004757648,0.0003570328,0.00001538394,0.0004587959,0.00007169532,0.0009775326,0.00001608046,0.00005655301,0.07907226,0.9186032,0.0001385877],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4172245,0.2922309,0.007885242,0.02660389,0.00724429,0.0006404083,0.00003051906,0.0004070823,0.2477332],"genre_scores_gemma":[0.9756911,0.01477485,0.002754906,0.0009513428,0.002870151,0.00001926729,0.000002412467,0.00004049972,0.002895516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9102358,"threshold_uncertainty_score":0.9902626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1137508228038605,"score_gpt":0.2736717279993742,"score_spread":0.1599209051955137,"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."}}