{"id":"W1970930727","doi":"10.7202/004015ar","title":"Translation Principles vs. Translator Strategies","year":2002,"lang":"en","type":"article","venue":"Meta Journal des traducteurs","topic":"Translation Studies and Practices","field":"Arts and Humanities","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Set (abstract data type); Function (biology); Equivalence (formal languages); Linguistics; Relation (database); Context (archaeology); Interpersonal communication; Process (computing); Translation (biology); Natural language processing; Artificial intelligence; Psychology; Programming language; Communication","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":[0.03676264,0.001282067,0.0009678832,0.003105064,0.003854393,0.01282368,0.0022666,0.007032456,0.007075012],"category_scores_gemma":[0.05546298,0.0011859,0.001201744,0.002485858,0.01713225,0.01654588,0.005619983,0.005600755,0.005140952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002769202,"about_ca_system_score_gemma":0.005088402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006138994,"about_ca_topic_score_gemma":0.0005869827,"domain_scores_codex":[0.9088915,0.06614576,0.005395454,0.006179506,0.01167935,0.001708504],"domain_scores_gemma":[0.9586635,0.02596788,0.003142303,0.006732141,0.004751067,0.0007432542],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009480559,0.0000706938,0.0008514985,0.0004461833,0.00004077774,0.0003099205,0.04391418,0.0005987653,0.002408964,0.9024252,0.00232252,0.04651642],"study_design_scores_gemma":[0.0002845008,0.0004270508,0.001568554,0.0007736068,0.0001592695,0.001830486,0.01878006,0.007344328,0.01050239,0.7986907,0.159519,0.0001200101],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06067153,0.002243277,0.5490507,0.03285739,0.0007950587,0.001316334,0.0001892106,0.001543197,0.3513333],"genre_scores_gemma":[0.7211745,0.001669911,0.2240438,0.004094439,0.0005505712,0.002545335,0.0002096835,0.00114593,0.04456581],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03676264,"threshold_uncertainty_score":0.1944218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1831839468528483,"score_gpt":0.2856793618918909,"score_spread":0.1024954150390426,"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."}}