{"id":"W4408639091","doi":"10.36078/1742363885","title":"ФАКТОРЫ, ОБУСЛОВЛИВАЮЩИЕ ВЫБОР GET-ПАССИВОВ В АНГЛИЙСКОМ ЯЗЫКЕ: КОРПУСНОЕ ИССЛЕДОВАНИЕ","year":2025,"lang":"en","type":"article","venue":"Foreign Languages in Uzbekistan","topic":"Syntax, Semantics, Linguistic Variation","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007575914,0.0003199256,0.0002330179,0.001517146,0.00217796,0.003589713,0.0003983093,0.0006282481,0.01449831],"category_scores_gemma":[0.001663963,0.0004326956,0.0002605946,0.001492225,0.003786711,0.001651399,0.0008532139,0.0009256283,0.002942115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00330283,"about_ca_system_score_gemma":0.003621082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05116172,"about_ca_topic_score_gemma":0.100223,"domain_scores_codex":[0.9993948,0.000109473,0.00002135268,0.00009373547,0.000289673,0.00009104087],"domain_scores_gemma":[0.9993993,0.0001524402,0.00008429632,0.0001067642,0.0001960004,0.00006120266],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00007864097,0.00002785169,0.003592252,0.0002756092,0.00001496403,0.001314224,0.01237698,0.0008971702,0.0156096,0.8300402,0.006498299,0.1292742],"study_design_scores_gemma":[0.00002441227,0.00004853368,0.02534862,0.0002185436,0.00004088825,0.002214815,0.006244433,0.001581915,0.01200075,0.1375942,0.8145835,0.00009934427],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2005687,0.01254015,0.1027727,0.004753375,0.0005242806,0.0001633372,0.0009711557,0.0004496988,0.6772565],"genre_scores_gemma":[0.8423185,0.00598027,0.04554872,0.0001863479,0.000102973,0.0001292197,0.000280651,0.0002250516,0.1052283],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05116172,"threshold_uncertainty_score":0.1017278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01399440365397889,"score_gpt":0.2669728288734294,"score_spread":0.2529784252194505,"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."}}