{"id":"W2808264262","doi":"","title":"Лев Бердников: Русский Галантный век в лицах и сюжетах: в 2 кн. Montreal: Accent Graphics Communications 2013, кн. 1–2","year":2015,"lang":"ru","type":"article","venue":"Przegląd Rusycystyczny / Русское обозрение / Russian Studies Review","topic":"Art, Technology, and Culture","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Stress (linguistics); Graphics; Linguistics; Computer science; Computer graphics (images); Speech recognition","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":[0.002106122,0.0005110852,0.0003017724,0.001865842,0.002848079,0.007294376,0.000734853,0.001397113,0.01274125],"category_scores_gemma":[0.00301944,0.0004448048,0.0003228475,0.002403814,0.006781933,0.004819044,0.001949527,0.002522458,0.003467562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004089645,"about_ca_system_score_gemma":0.007421345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0247797,"about_ca_topic_score_gemma":0.04391395,"domain_scores_codex":[0.9983865,0.0005046341,0.0000789476,0.0001876656,0.0006289314,0.000213389],"domain_scores_gemma":[0.9987971,0.0004488686,0.0001477422,0.0001168979,0.0003587878,0.0001306065],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008402851,0.00002943499,0.001438304,0.000778251,0.0000206731,0.0003633504,0.01232855,0.000205704,0.001032115,0.6383026,0.08056062,0.2648564],"study_design_scores_gemma":[0.000007115382,0.00002467207,0.002155458,0.0005641021,0.00001564054,0.0003887725,0.003521665,0.00005822554,0.000640146,0.02819848,0.9644027,0.00002302883],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.01566011,0.4326017,0.009527364,0.03174227,0.005840315,0.0001005405,0.0003597655,0.0002212779,0.5039466],"genre_scores_gemma":[0.459644,0.2955039,0.01441202,0.004074508,0.002969921,0.0002516359,0.000317595,0.0002581433,0.2225681],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.0247797,"threshold_uncertainty_score":0.04927093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.134658428985726,"score_gpt":0.3450208032104986,"score_spread":0.2103623742247726,"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."}}