{"id":"W2167742478","doi":"10.1017/s1351324911000210","title":"Exploring patterns in dictionary definitions for synonym extraction","year":2011,"lang":"en","type":"article","venue":"Natural Language Engineering","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Synonym (taxonomy); Natural language processing; Artificial intelligence; Lexicon; Quality (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":[0.0001430908,0.0001477046,0.0001213898,0.0003074342,0.00005360972,0.00004709819,0.0003788636,0.00006195451,0.00001091717],"category_scores_gemma":[0.0001186929,0.0001442725,0.00006265164,0.0003179335,0.000005960424,0.001381437,0.0000828646,0.0003236471,0.000003908599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001110221,"about_ca_system_score_gemma":0.00001473861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001012824,"about_ca_topic_score_gemma":0.00002232096,"domain_scores_codex":[0.9991185,0.00001093818,0.0001869471,0.0002708405,0.0001321802,0.0002806109],"domain_scores_gemma":[0.9995325,0.00009729845,0.0000443607,0.0002402091,0.00003996166,0.00004565284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000757608,0.0003454035,0.002064463,0.0007307218,0.00009179658,0.0008692913,0.02593921,0.0005872071,0.1771531,0.2276152,0.0001242953,0.5644035],"study_design_scores_gemma":[0.002017972,0.0003342804,0.0424717,0.001525494,0.00005106309,0.0006901466,0.001433744,0.3691351,0.571402,0.007170641,0.0009548017,0.002813138],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1289871,0.003951296,0.864161,0.00006982639,0.0009628681,0.000279678,0.000009429573,0.001419859,0.0001588658],"genre_scores_gemma":[0.6790269,0.00002282471,0.3206642,0.00002936272,0.00007252603,0.0001420856,0.000009631547,0.00001424152,0.00001824985],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5615904,"threshold_uncertainty_score":0.5883261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07898671688241453,"score_gpt":0.262412322812195,"score_spread":0.1834256059297805,"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."}}