{"id":"W2795863322","doi":"10.7202/1050522ar","title":"Constraints on Opera Surtitling: Hindrance or Help?","year":2018,"lang":"en","type":"article","venue":"Meta Journal des traducteurs","topic":"Translation Studies and Practices","field":"Arts and Humanities","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Constraint (computer-aided design); Opera; Scope (computer science); Relevance (law); Process (computing); Computer science; Modality (human–computer interaction); Term (time); Quality (philosophy); Epistemology; Political science; Artificial intelligence; Engineering; Law; History; 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":[0.0004440014,0.0001661859,0.0002687277,0.00008048597,0.001011345,0.0004805603,0.0001721174,0.0000252287,0.01981774],"category_scores_gemma":[0.00005081784,0.0001000871,0.0001579204,0.00005059322,0.0009055377,0.0005037971,0.000008185304,0.0002671581,0.0003762876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001500051,"about_ca_system_score_gemma":0.00003847325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002569568,"about_ca_topic_score_gemma":0.0004869621,"domain_scores_codex":[0.9989067,0.0001221934,0.0003008052,0.0001623474,0.0002533688,0.0002546396],"domain_scores_gemma":[0.999254,0.0001772007,0.000144708,0.0001229303,0.0002000298,0.0001010841],"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":[0.0004906761,0.000192908,0.000189709,0.00002987029,0.001839031,0.0000779812,0.0128977,0.00001336253,0.0001724708,0.05738511,0.0114392,0.915272],"study_design_scores_gemma":[0.0003829201,0.0003686142,0.0003285691,0.00002835615,0.00029874,0.0001108546,0.0005990248,0.000006249055,0.0002513145,0.001810174,0.9956604,0.000154813],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3701901,0.08227722,0.003179065,0.01473411,0.0143073,0.0006619907,0.0002007675,0.0003318648,0.5141176],"genre_scores_gemma":[0.9755038,0.01077961,0.0008137154,0.001337731,0.003546741,0.000005543735,0.000001808664,0.00003476819,0.007976308],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9842212,"threshold_uncertainty_score":0.9810783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1516735533297848,"score_gpt":0.3163438537052233,"score_spread":0.1646703003754384,"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."}}