{"id":"W4280597102","doi":"10.1075/term.20044.san","title":"Repérage automatisé de l’hyponymie dans des corpus spécialisés en français à l’aide de Sketch Engine","year":2022,"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":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Computer science; Sketch; Natural language processing; Artificial intelligence; Terminology; Grammar; Linguistics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000899522,0.0001434093,0.0003294611,0.0002229594,0.0003415624,0.00007179013,0.0008568159,0.00006790716,0.001280468],"category_scores_gemma":[0.0003195075,0.0001324045,0.00007194773,0.00003598736,0.001620576,0.0000618497,0.0005147411,0.0005117984,0.000004135135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000199488,"about_ca_system_score_gemma":0.00004485757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000162708,"about_ca_topic_score_gemma":0.0001447469,"domain_scores_codex":[0.9985341,0.0003225103,0.0005600093,0.0001325441,0.0002214543,0.0002294198],"domain_scores_gemma":[0.9988156,0.0005168889,0.0002638293,0.0002150026,0.0001385316,0.00005016286],"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":[0.0002593385,0.0001709132,0.002421786,0.000006833618,0.0001235136,0.00008437913,0.0399942,0.00003469776,0.000241291,0.9412117,0.0003159991,0.01513534],"study_design_scores_gemma":[0.001622543,0.0001883978,0.01088138,0.00004970434,0.00008023668,0.0004430373,0.005870581,0.0006158193,0.0007908772,0.8915563,0.08767968,0.0002214459],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9348896,0.001175573,0.0002622647,0.004875748,0.0006337716,0.0001250146,0.00002956708,0.00003921162,0.05796923],"genre_scores_gemma":[0.9942857,0.001076876,0.003225022,0.0004169083,0.0007019209,0.00003024653,0.00001533306,0.00001586438,0.000232104],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08736369,"threshold_uncertainty_score":0.9996325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0217718389393975,"score_gpt":0.2837191263970931,"score_spread":0.2619472874576956,"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."}}