{"id":"W3196747493","doi":"10.1093/ijl/ecab018","title":"Converging Lexicography and Neology","year":2021,"lang":"en","type":"article","venue":"International Journal of Lexicography","topic":"Lexicography and Language Studies","field":"Arts and Humanities","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canarie","funders":"","keywords":"Lexicography; Neologism; Linguistics; Czech; Context (archaeology); Computer science; Slavic languages; Portuguese; Slovak; Romance languages; Representation (politics); Lexicographical order; Prefix; History; Natural language processing; Mathematics; Political science; Philosophy; Politics","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":[0.0002031049,0.0001559764,0.0002516034,0.0006794106,0.0001553725,0.0002317407,0.0002563496,0.0000443957,0.0009351726],"category_scores_gemma":[0.00006509976,0.0001316066,0.0004062744,0.0001266784,0.0005738806,0.0003717999,0.00008766382,0.0002473833,0.000004595774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001021331,"about_ca_system_score_gemma":0.00004694445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004014754,"about_ca_topic_score_gemma":0.0001341557,"domain_scores_codex":[0.9987566,0.0000601679,0.0004448916,0.0001647551,0.0003859574,0.0001875858],"domain_scores_gemma":[0.9983187,0.000135624,0.0003158326,0.00009958136,0.001041612,0.0000886544],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004924373,0.0008060484,0.171634,0.00008425137,0.006796567,0.0035809,0.09970384,0.00002031431,0.002019394,0.6389511,0.01886816,0.0570429],"study_design_scores_gemma":[0.00231476,0.0003218233,0.01848968,0.0002175841,0.0001924785,0.001182377,0.01941768,0.00001539624,0.001759384,0.02987856,0.925759,0.0004512334],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9232067,0.01439268,0.0003427068,0.005878972,0.005944987,0.00006607913,0.00004663672,0.00005109414,0.05007009],"genre_scores_gemma":[0.9953779,0.0009431337,0.0004242496,0.00154537,0.00142578,0.000002219506,0.000006746442,0.00001348399,0.0002611092],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9068909,"threshold_uncertainty_score":0.9999781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01275976097725464,"score_gpt":0.2358028687691651,"score_spread":0.2230431077919105,"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."}}