{"id":"W4385239993","doi":"10.1075/term.22017.lho","title":"Managing polysemy in terminological resources*","year":2023,"lang":"en","type":"article","venue":"Terminology International Journal of Theoretical and Applied Issues in Specialized Communication","topic":"linguistics and terminology studies","field":"Arts and Humanities","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Polysemy; Categorization; Terminology; Linguistics; Ambiguity; Vagueness; Phenomenon; Semantics (computer science); Computer science; Perspective (graphical); Artificial intelligence; Epistemology; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005146363,0.0001283332,0.0003408141,0.0005517875,0.00008855222,0.00007358036,0.0006971056,0.00009047685,0.0003151876],"category_scores_gemma":[0.0001986934,0.0001041342,0.00005071593,0.00006495302,0.001542503,0.00006429071,0.0004076601,0.0003730944,0.00002370723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004346417,"about_ca_system_score_gemma":0.00001009524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002593577,"about_ca_topic_score_gemma":0.00006670393,"domain_scores_codex":[0.9987378,0.0001191007,0.0006067271,0.0001454183,0.0001822077,0.000208737],"domain_scores_gemma":[0.9991052,0.0003647201,0.0002161115,0.0001792599,0.0001033587,0.00003134947],"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":[0.0002335129,0.00007651416,0.001490087,0.000004192508,0.00004317989,0.0001057429,0.009361111,0.0000041981,0.00004245175,0.9635202,0.0002812179,0.02483753],"study_design_scores_gemma":[0.001498653,0.00009652586,0.009255566,0.00009503575,0.00002054572,0.00005356945,0.003237183,0.0002085036,0.000108845,0.9242654,0.06099088,0.0001692188],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8946856,0.0005970001,0.000006582304,0.01743371,0.0006193455,0.0001069126,0.000005568171,0.00003851025,0.08650681],"genre_scores_gemma":[0.9960777,0.002514577,0.0002764762,0.0003101734,0.0005356334,0.00001093744,0.000008259913,0.000009293022,0.000256992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1013921,"threshold_uncertainty_score":0.5683416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03268050873585338,"score_gpt":0.3116059266293812,"score_spread":0.2789254178935279,"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."}}