{"id":"W2275805726","doi":"","title":"ИНФОРМАЦИОННЫЙ МЕНЕДЖМЕНТ И УПРАВЛЕНИЕ ГОСУДАРСТВЕННОЙ ИНФОРМАЦИЕЙ КАК КОМПОНЕНТЫ ГОСУДАРСТВЕННОЙ ИНФОРМАЦИОННОЙ ПОЛИТИКИ КАНАДЫ","year":2013,"lang":"ru","type":"article","venue":"Исторические, философские, политические и юридические науки, культурология и искусствоведение. Вопросы теории и практики","topic":"Information Architecture and Usability","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Realia; Politics; Administration (probate law); Political science; Information policy; Public administration; Public relations; Computer science; Law; Library 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"category_scores_codex":[0.01117494,0.01436051,0.01250732,0.007604399,0.008484295,0.01310477,0.02503504,0.008058029,0.03844746],"category_scores_gemma":[0.004711532,0.01468388,0.008354764,0.01589022,0.006947559,0.01968252,0.01260843,0.01510814,0.09203092],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.00622895,"about_ca_system_score_gemma":0.009630192,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009774722,"about_ca_topic_score_gemma":0.003889134,"domain_scores_codex":[0.9280809,0.006286151,0.01831331,0.01467501,0.01362472,0.01901991],"domain_scores_gemma":[0.9439033,0.004789981,0.009796503,0.0219556,0.008627648,0.01092693],"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":[0.00240239,0.01018922,0.01105744,0.005345702,0.005382868,0.001417037,0.02324459,0.005407657,0.009296387,0.05877672,0.6083763,0.2591037],"study_design_scores_gemma":[0.02782168,0.007427717,0.05846656,0.004946539,0.003713991,0.004590141,0.006614441,0.06796478,0.02188021,0.07007466,0.6929511,0.03354814],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3360934,0.02458894,0.1106238,0.06151823,0.05762446,0.04405031,0.00796629,0.02117064,0.3363639],"genre_scores_gemma":[0.8862845,0.00257748,0.02327207,0.03509923,0.008596869,0.005148625,0.00352294,0.002482342,0.03301594],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5501911,"threshold_uncertainty_score":0.997586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01063118814037715,"score_gpt":0.2247455490812726,"score_spread":0.2141143609408954,"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."}}