{"id":"W2261324480","doi":"","title":"Исследование Возможностей И Диапазонов Применения Методологии Экономико-Математического Моделирования На Основе Тензорного Анализа Денежного Поля: Теоретические И Методологические Вопросы Взаимодействия Финансового И Реального Сектора Экономики [The research of possibilities and scope for application of economically-mathematical modeling methodology in terms of money field tensor analysis: theoretical and methodological questions of interaction between financial and real sectors of an economy]","year":2012,"lang":"ru","type":"article","venue":"MPRA Paper","topic":"Economic Theory and Policy","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Scope (computer science); Order (exchange); Field (mathematics); Economics; Macroeconomics; Econometric model; Stability (learning theory); Financial stability; Finance; Econometrics; Computer science; Financial system; Mathematics","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"],"consensus_categories":[],"category_scores_codex":[0.01505981,0.0006001514,0.003368624,0.001438232,0.0001913223,0.00005697434,0.0006535837,0.00100729,0.0003544221],"category_scores_gemma":[0.004414244,0.0005673128,0.0005070897,0.0006646261,0.002596374,0.000842494,0.0004778601,0.0008593466,0.000004490949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001401904,"about_ca_system_score_gemma":0.000145502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002382934,"about_ca_topic_score_gemma":0.0005772517,"domain_scores_codex":[0.9915243,0.001980795,0.004312951,0.001151787,0.0001188092,0.0009113801],"domain_scores_gemma":[0.9828808,0.01354042,0.00176538,0.001191039,0.0002828992,0.0003394416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001775973,0.0008119605,0.1230997,0.001928127,0.0009161256,6.644731e-7,0.007235821,0.001257204,0.001935905,0.849599,0.00001600971,0.01142356],"study_design_scores_gemma":[0.002687662,0.002937233,0.1253095,0.0004658718,0.001318866,0.00003141252,0.004332643,0.06308006,0.009237912,0.7893719,0.0001581496,0.00106879],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9793547,0.001434275,0.01382549,0.0004972712,0.0001405023,0.001385795,0.0008882133,0.00001555191,0.002458235],"genre_scores_gemma":[0.9862356,0.001348235,0.01173233,0.0000698367,0.0002630258,0.0001736829,0.00005938881,0.00006371954,0.00005420058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06182285,"threshold_uncertainty_score":0.9996778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2278678105060801,"score_gpt":0.4257305794566109,"score_spread":0.1978627689505307,"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."}}