{"id":"W2067366489","doi":"10.7202/1027474ar","title":"Evidence of Parallel Processing During Translation","year":2014,"lang":"en","type":"article","venue":"Meta Journal des traducteurs","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Source text; Reading (process); Natural language processing; Literal translation; Eye tracking; Congruence (geometry); Machine translation; Artificial intelligence; Linguistics; Translation (biology); Danish; Target text; Example-based machine translation; Psychology","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":[0.003494252,0.0004962232,0.0006977012,0.0006326275,0.0006100644,0.001804906,0.0006208494,0.001118301,0.006460144],"category_scores_gemma":[0.04199081,0.001000636,0.0005473283,0.0005851809,0.001612962,0.00383386,0.001596547,0.001259485,0.001273962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005191342,"about_ca_system_score_gemma":0.0006947546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001687677,"about_ca_topic_score_gemma":0.001618292,"domain_scores_codex":[0.9961803,0.001180821,0.0003079873,0.001475204,0.00065111,0.0002046196],"domain_scores_gemma":[0.9681425,0.02030252,0.003505707,0.005480547,0.002064156,0.0005045342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.009504638,0.001626761,0.08587511,0.002236335,0.0005992922,0.001924621,0.0309761,0.002397393,0.6406592,0.01223975,0.00164791,0.2103129],"study_design_scores_gemma":[0.001554996,0.004189473,0.73194,0.000253781,0.0005948113,0.004164983,0.004061167,0.01957839,0.175388,0.05015469,0.007821791,0.00029801],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9740097,0.000303545,0.01391278,0.0002284209,0.00003611766,0.0001325751,0.0002078904,0.0001947088,0.01097428],"genre_scores_gemma":[0.9901759,0.000127829,0.008074903,0.0001078531,0.00001775155,0.0001387401,0.000195542,0.00008350705,0.001077887],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006460144,"threshold_uncertainty_score":0.02161127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05663297699258963,"score_gpt":0.2992657555134165,"score_spread":0.2426327785208269,"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."}}