{"id":"W2322334754","doi":"10.1093/ijl/ecu019","title":"Why Lexical Semantics is Important for E-Lexicography and Why it is Equally Important to Hide its Formal Representations from Users of Dictionaries","year":2014,"lang":"en","type":"article","venue":"International Journal of Lexicography","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Lexicography; Semantics (computer science); Linguistics; Lexical semantics; Computer science; Lexical item; Philosophy; Programming language","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006741931,0.0002360044,0.0003713068,0.001074735,0.0001269314,0.0003301181,0.00133985,0.0001199373,0.00002033886],"category_scores_gemma":[0.000336022,0.0002048561,0.0004366098,0.0005681444,0.000138804,0.001459265,0.0002816701,0.0002590236,4.897893e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002878989,"about_ca_system_score_gemma":0.00009140941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001033366,"about_ca_topic_score_gemma":0.00003808895,"domain_scores_codex":[0.9970174,0.00004771831,0.001246961,0.0003700261,0.001032753,0.0002850701],"domain_scores_gemma":[0.9964965,0.0003821674,0.001100694,0.0003067106,0.00150058,0.0002133321],"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":[0.001841287,0.00137345,0.2815839,0.0002349529,0.004031987,0.0001981683,0.01823096,0.00009804519,0.06476903,0.3035894,0.286804,0.03724478],"study_design_scores_gemma":[0.003496907,0.002327689,0.01953455,0.001028112,0.0003272636,0.0004666544,0.0006323627,0.01998814,0.1832861,0.6657081,0.1019505,0.001253723],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05429364,0.001401725,0.9045101,0.03848749,0.0007389849,0.0002387839,0.0001950639,0.00007498061,0.00005923638],"genre_scores_gemma":[0.6714163,0.0002175305,0.3149394,0.01308645,0.0002805775,0.00001401822,0.00001479102,0.0000200807,0.00001082032],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6171227,"threshold_uncertainty_score":0.8353788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01875754665328462,"score_gpt":0.3139004244293343,"score_spread":0.2951428777760497,"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."}}