{"id":"W2258058221","doi":"","title":"О политических рисках гражданского общества в современной России","year":2014,"lang":"ru","type":"article","venue":"Теория и практика общественного развития","topic":"Security, Politics, and Digital Transformation","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sanctions; Foreign policy; Civil society; Political science; State (computer science); Terrorism; Economic sanctions; Politics; Context (archaeology); Political economy; Public administration; Economics; Law","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","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.003458438,0.001706528,0.001891377,0.0008220195,0.002389188,0.001967938,0.002484037,0.001616836,0.003232291],"category_scores_gemma":[0.00188348,0.001841957,0.001261335,0.001435258,0.002567253,0.003272393,0.0003993414,0.001519622,0.009453575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008853891,"about_ca_system_score_gemma":0.001216832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006212577,"about_ca_topic_score_gemma":0.003290089,"domain_scores_codex":[0.9868137,0.001322241,0.002706871,0.002052887,0.003115304,0.003989055],"domain_scores_gemma":[0.9925964,0.001345794,0.001068913,0.001961917,0.0008855669,0.002141437],"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":[0.0003845934,0.002651394,0.01807746,0.001491409,0.0006416967,0.00007785824,0.08211522,0.0001234347,0.0003126746,0.7325446,0.07186954,0.08971012],"study_design_scores_gemma":[0.003694891,0.0009159468,0.006820602,0.0005899445,0.0005068949,0.0000444536,0.01184965,0.002055935,0.001359257,0.06350345,0.9055083,0.003150634],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.186124,0.002443499,0.002958748,0.007927725,0.01038681,0.002131941,0.0005530519,0.001513744,0.7859604],"genre_scores_gemma":[0.9674929,0.001329171,0.000455021,0.004498654,0.005650415,0.0001094432,0.0003577866,0.0002660988,0.01984052],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8336388,"threshold_uncertainty_score":0.9996793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03109829625246382,"score_gpt":0.3075217455044806,"score_spread":0.2764234492520168,"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."}}