{"id":"W4400283448","doi":"10.55959/msu2070-1381-104-2024-147-161","title":"Foreign Experience in Digitalization of Preventive Public Financial Control (on the Example of USA, China, Canada, India and Australia)","year":2024,"lang":"en","type":"article","venue":"Государственное управление Электронный вестник","topic":"Economic and Technological Developments in Russia","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Control (management); Business; Finance; Economic growth; Political science; Economics; Management","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":[],"consensus_categories":[],"category_scores_codex":[0.0007643582,0.0001764238,0.0003189009,0.0001567577,0.0001945181,0.00008894883,0.0004390128,0.0001764975,0.000573977],"category_scores_gemma":[0.0006676432,0.0001350353,0.0000581614,0.000532334,0.0007138139,0.0003371949,0.00008186259,0.0002217963,0.000008087211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002180188,"about_ca_system_score_gemma":0.0007429912,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2266973,"about_ca_topic_score_gemma":0.2816412,"domain_scores_codex":[0.998179,0.0001461488,0.0005343236,0.0003723001,0.0003579732,0.0004102987],"domain_scores_gemma":[0.9990445,0.0004009578,0.0001906368,0.0002241049,0.00004992948,0.00008989208],"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":[0.00001593901,0.00005422788,0.1457777,0.00003336905,0.00002493581,0.000009840447,0.003203267,0.000007396327,0.00002694763,0.8445606,0.001935792,0.004350006],"study_design_scores_gemma":[0.0005343474,0.0001400538,0.8992933,0.0002473695,0.00001838455,0.000002554639,0.002744104,0.00009090708,0.001008432,0.0600592,0.03548282,0.0003785221],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9767134,0.0001557252,0.0002788587,0.0008953062,0.0002552912,0.0005435858,0.00007137052,0.00003091398,0.02105553],"genre_scores_gemma":[0.9985032,0.00007637322,0.00007717732,0.0001162792,0.0000397239,0.00008228987,0.000007394047,0.00001069917,0.001086846],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7845013,"threshold_uncertainty_score":0.7784522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04924356103649437,"score_gpt":0.2846502658466948,"score_spread":0.2354067048102005,"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."}}