{"id":"W483512959","doi":"","title":"Englisches Lehngut in der Russischen Fachsprache Des Marketings Und Des Außenhandels","year":2005,"lang":"de","type":"article","venue":"Canadian Slavonic Papers","topic":"Linguistics, Language Diversity, and Identity","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Political science","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":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007384615,0.0004827549,0.0004692482,0.0005183804,0.001359604,0.0007656913,0.00054948,0.0002908436,0.007816268],"category_scores_gemma":[0.004874574,0.0005162839,0.0002453713,0.0001618573,0.001303996,0.0004895942,0.0001105187,0.0005699258,0.001026368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001585668,"about_ca_system_score_gemma":0.001079671,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3536949,"about_ca_topic_score_gemma":0.9456515,"domain_scores_codex":[0.9969855,0.0002200246,0.0005011957,0.0006114242,0.0003020327,0.001379846],"domain_scores_gemma":[0.9977903,0.0001845005,0.0001469359,0.000413937,0.000582627,0.0008816434],"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":[0.0001441685,0.0004019917,0.196589,0.0009821592,0.00219303,0.0009210466,0.6590514,0.0001097491,0.00004306713,0.0191765,0.07107913,0.04930882],"study_design_scores_gemma":[0.001097882,0.00006035265,0.01886692,0.0003459712,0.0006437983,0.000001107377,0.05385178,0.00009215425,0.00007693555,0.0005755752,0.9234107,0.0009767851],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7488678,0.0494037,0.000002236224,0.0002310701,0.00502063,0.0003545859,0.0004789095,0.00007274894,0.1955683],"genre_scores_gemma":[0.9691725,0.001523753,0.0002544858,0.001031153,0.009832679,0.000009959176,0.00008030845,0.00006309825,0.01803211],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8523316,"threshold_uncertainty_score":0.9999405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02330873614371285,"score_gpt":0.2300423584807072,"score_spread":0.2067336223369944,"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."}}