{"id":"W2104444209","doi":"10.5539/elt.v2n3p53","title":"Text Coherence in Translation","year":2009,"lang":"en","type":"article","venue":"English Language Teaching","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Foregrounding; Coherence (philosophical gambling strategy); Source text; Target text; Translation (biology); Natural language processing; Computer science; Linguistics; Artificial intelligence; Complement (music); Process (computing); Space (punctuation); Psychology; Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005315159,0.0006536189,0.0006375654,0.003296448,0.003413032,0.006258308,0.001041534,0.002115801,0.011535],"category_scores_gemma":[0.02908843,0.0005870719,0.0008032446,0.004150627,0.01002092,0.01621294,0.006639968,0.002557069,0.001893938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002573396,"about_ca_system_score_gemma":0.001792642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001511379,"about_ca_topic_score_gemma":0.0008957313,"domain_scores_codex":[0.9915405,0.005125001,0.0005690826,0.001272121,0.001127045,0.0003662],"domain_scores_gemma":[0.9825117,0.01188187,0.001351778,0.001916218,0.001928154,0.0004103916],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000140088,0.00002378252,0.0006742039,0.0003795548,0.00003052327,0.0003566458,0.01141207,0.002026082,0.001259271,0.9203783,0.005822533,0.05749679],"study_design_scores_gemma":[0.00007189895,0.0001022807,0.00108457,0.0002268034,0.0000521072,0.0004990105,0.004931962,0.008925461,0.002804586,0.8895084,0.09174627,0.00004672481],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06610936,0.01459165,0.639264,0.02983965,0.002666572,0.0004501495,0.000603905,0.001057129,0.2454176],"genre_scores_gemma":[0.8488727,0.003347686,0.1197993,0.001626649,0.001676664,0.0004477758,0.0005854222,0.0005443875,0.02309931],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.011535,"threshold_uncertainty_score":0.0385884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009913382092200971,"score_gpt":0.2732470129008626,"score_spread":0.2633336308086616,"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."}}