{"id":"W3083565174","doi":"10.1093/ijl/ecaa015","title":"‘Alien’ vs. Editor: World English in the<i>Oxford English Dictionary</i>, Policies, Practices, and Outcomes 1884–2020","year":2020,"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":"University of Waterloo; St. Jerome's University","funders":"","keywords":"Lexicography; Section (typography); Linguistics; Vocabulary; Alien; State (computer science); History; Computer science; English language; Artificial intelligence; Political science; Law; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007036074,0.0001515262,0.0002125655,0.002314316,0.002059804,0.008576686,0.0003431197,0.000706481,0.01029568],"category_scores_gemma":[0.02376523,0.0001531027,0.00007870402,0.003928628,0.005419794,0.004837933,0.002596838,0.001404075,0.001765172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004507969,"about_ca_system_score_gemma":0.004694926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01705626,"about_ca_topic_score_gemma":0.02593779,"domain_scores_codex":[0.9933801,0.00303691,0.0007321403,0.0005698881,0.001660233,0.0006206635],"domain_scores_gemma":[0.9765296,0.01125476,0.003475984,0.0009804313,0.005027251,0.002731994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005026364,0.00006215678,0.02076614,0.001515353,0.00002233489,0.00103606,0.2188953,0.0002281397,0.001949043,0.2513995,0.2957386,0.2078847],"study_design_scores_gemma":[0.00001689138,0.00003619735,0.02490947,0.0006811547,0.00000782348,0.0002148926,0.04203865,0.00006865395,0.0006849886,0.003001987,0.9283054,0.00003389205],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3204242,0.0461796,0.001783308,0.1779984,0.009610494,0.00007545928,0.002061107,0.0002196243,0.4416479],"genre_scores_gemma":[0.9084371,0.008768489,0.00109046,0.006468145,0.001262003,0.00003488385,0.0004645006,0.0002262716,0.07324823],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01705626,"threshold_uncertainty_score":0.03721076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0218503297589439,"score_gpt":0.2708038437703744,"score_spread":0.2489535140114305,"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."}}