{"id":"W4412360114","doi":"10.5430/wjel.v16n1p17","title":"A Multidimensional Analysis of Linguistic Variation in Russian and British Newspaper Editorials","year":2025,"lang":"en","type":"article","venue":"World Journal of English Language","topic":"Lexicography and Language Studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Newspaper; Variation (astronomy); Linguistics; Computer science; Political science; Astrophysics; Physics; Law; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004016353,0.00008125998,0.0003667493,0.0009070169,0.00006876282,0.00006374939,0.0000692238,0.00002592156,0.0004558066],"category_scores_gemma":[0.001023221,0.00007312752,0.0001555418,0.0003702057,0.0000948392,0.000106038,0.00002758704,0.0001509242,2.334581e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001739577,"about_ca_system_score_gemma":0.00002947617,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001173827,"about_ca_topic_score_gemma":0.02247401,"domain_scores_codex":[0.9991168,0.00006356491,0.0004533087,0.00009405654,0.0001642434,0.0001080717],"domain_scores_gemma":[0.9990988,0.0002522548,0.0002362639,0.00007406472,0.0003085364,0.00003005051],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001576464,0.0003484499,0.01698492,0.0001266401,0.002982663,0.0002165818,0.8512059,0.00009958759,0.000246675,0.1201716,0.004348671,0.003110699],"study_design_scores_gemma":[0.007272298,0.0003080769,0.4247353,0.002668791,0.006706265,0.000005221518,0.1035078,0.0002197029,0.0001831694,0.003939896,0.4495735,0.0008799416],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9144126,0.01163516,0.00002392125,0.0001023515,0.00826409,0.0001131086,0.0000608118,0.00001580058,0.06537212],"genre_scores_gemma":[0.9946756,0.00007042406,0.0002418681,0.0000906019,0.00384629,0.000001423217,0.000005042857,0.000004308728,0.001064388],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7476981,"threshold_uncertainty_score":0.9953633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005851389533152023,"score_gpt":0.2347639044528992,"score_spread":0.2289125149197471,"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."}}