{"id":"W2955521332","doi":"","title":"2015.03.028. ХЕТЕНЬИ З., СТЕРН Л. В ПОИСКАХ КЛЮЧА, СПРЯТАННОГО ЦЕНЗОРОМ: О РАССКАЗЕ ВАСИЛИЯ ГРОССМАНА «В КИСЛОВОДСКЕ». HETéNYI Z., STERN L. RECOVERING THE KEY THE CENSOR HID: ON VASILY GROSSMAN’S «IN KISLOVODSK» // TORONTO SLAVIC QUATERLY. - TORONTO, 2014. - N 49. - P. 25-37","year":2015,"lang":"ru","type":"article","venue":"Социальные и гуманитарные науки. Отечественная и зарубежная литература. Сер. 7, Литературоведение: Реферативный журнал","topic":"European Cultural and National Identity","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Grossman; Stern; Key (lock); Linguistics; Art; History; Philosophy; Computer science; Ancient history","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":["metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","sts","research_integrity","insufficient_payload"],"category_scores_codex":[0.01741765,0.006207538,0.005335676,0.00080163,0.007308519,0.005940222,0.01338929,0.003175634,0.01031903],"category_scores_gemma":[0.003884556,0.004670989,0.0036803,0.003677318,0.004376482,0.01048566,0.003897838,0.006275089,0.02137291],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01256831,"about_ca_system_score_gemma":0.00355071,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1300211,"about_ca_topic_score_gemma":0.3749041,"domain_scores_codex":[0.9553418,0.009531713,0.007860115,0.007384721,0.01100103,0.008880649],"domain_scores_gemma":[0.9756024,0.004456668,0.005057195,0.007604935,0.003132775,0.004145998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.006869489,0.009467689,0.03283083,0.001415605,0.004538835,0.002454006,0.1370088,0.00278337,0.003539891,0.05430939,0.705,0.03978205],"study_design_scores_gemma":[0.0122914,0.003635616,0.090376,0.002299147,0.001878586,0.0005072361,0.05511165,0.001704713,0.0008851237,0.006690325,0.815207,0.00941319],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5666018,0.08628356,0.0002016296,0.04392003,0.03853879,0.01581599,0.003079579,0.003152413,0.2424062],"genre_scores_gemma":[0.859318,0.02188593,0.00057435,0.006941915,0.01280133,0.001144689,0.0009228722,0.001332778,0.09507817],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2927162,"threshold_uncertainty_score":0.998333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05258530648185569,"score_gpt":0.3220227111478479,"score_spread":0.2694374046659922,"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."}}