{"id":"W2135798047","doi":"10.7202/012993ar","title":"Arabic Imperfect Verbs in Translation: A Corpus Study of English Renderings","year":2006,"lang":"en","type":"article","venue":"Meta Journal des traducteurs","topic":"Translation Studies and Practices","field":"Arts and Humanities","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Imperfect; Arabic; Linguistics; Computer science; Natural language processing; Artificial intelligence; 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":[0.002506725,0.0002996163,0.0003738063,0.002031879,0.002518688,0.001919305,0.0004264905,0.0004607376,0.002787746],"category_scores_gemma":[0.01217829,0.0002633945,0.0001468198,0.004398041,0.00242158,0.002523274,0.001604689,0.001011287,0.0003266571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001028314,"about_ca_system_score_gemma":0.0007468374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00555157,"about_ca_topic_score_gemma":0.01017082,"domain_scores_codex":[0.9984383,0.0009632799,0.0001542209,0.0001574771,0.0002289848,0.00005772782],"domain_scores_gemma":[0.989636,0.00786999,0.0009119827,0.0006538723,0.0008089148,0.0001192657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0004371997,0.0003771224,0.0339435,0.001606322,0.00004467789,0.004592534,0.8154398,0.0005081844,0.01228175,0.03277527,0.006645157,0.09134852],"study_design_scores_gemma":[0.0001593208,0.0003366477,0.1964813,0.001214251,0.0001779363,0.007884818,0.5087735,0.005721832,0.0151621,0.008092812,0.2558669,0.0001285068],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9802698,0.001260209,0.003247309,0.0004605651,0.00004520976,0.0001028485,0.0005212753,0.0000289666,0.01406387],"genre_scores_gemma":[0.9943911,0.0006624606,0.003096225,0.00005514856,0.00002434179,0.0000778843,0.0004737003,0.00005261524,0.001166499],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00555157,"threshold_uncertainty_score":0.01325697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06901195109852859,"score_gpt":0.2666832026034535,"score_spread":0.1976712515049249,"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."}}