{"id":"W2507326027","doi":"10.18522/1995-0640-2016-2-192-203","title":"Structural-Semantic Peculiarities of Derogatory Marked Ethnonyms of the Canadian, Australian and New Zealand English Language","year":2016,"lang":"en","type":"article","venue":"Proceedings of Southern Federal University Philology","topic":"Lexicography and Language Studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Linguistics; Computer science; Word formation; Artificial intelligence; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007061327,0.0001115119,0.0002207117,0.0001267573,0.0002488221,0.00001560053,0.000194701,0.00007239069,0.000279812],"category_scores_gemma":[0.00004162009,0.00007157806,0.00008578232,0.00004466086,0.001112973,0.0001160439,0.00007539304,0.00008383458,7.816015e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002212382,"about_ca_system_score_gemma":0.00005004294,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08297914,"about_ca_topic_score_gemma":0.1572885,"domain_scores_codex":[0.9994398,0.0000118465,0.0001359891,0.0001344046,0.00009720868,0.0001807563],"domain_scores_gemma":[0.9994522,0.00003537546,0.0001761851,0.00005635756,0.0002122085,0.00006763504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002088892,0.00002480572,0.2196007,0.000331288,0.0004257132,0.000005832596,0.658278,1.239078e-7,0.002991912,0.1135259,0.003666249,0.0009405407],"study_design_scores_gemma":[0.003780741,0.0003930488,0.05190308,0.0005739836,0.0003465614,0.00001061254,0.8923486,0.000001557832,0.004607601,0.01097931,0.03443962,0.0006152912],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9872743,0.0001027757,7.339331e-8,0.001158956,0.00008302359,0.00009944088,0.0001640983,0.00001522762,0.01110203],"genre_scores_gemma":[0.9886136,0.00001366126,0.00001457908,0.0000335424,0.00009345961,1.664175e-7,8.817814e-7,0.000006566461,0.01122351],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2340705,"threshold_uncertainty_score":0.9231274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01699902485975404,"score_gpt":0.1846875733498485,"score_spread":0.1676885484900945,"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."}}