{"id":"W4415346474","doi":"10.34925/eip.2025.182.9.260","title":"ГОСУДАРСТВЕННАЯ ПОДДЕРЖКА ЦИФРОВОГО СЕЛЬСКОГО ХОЗЯЙСТВА НА ЗАПАДЕ: РЕКОМЕНДАЦИИ ДЛЯ СТРАН С ФОРМИРУЮЩЕЙСЯ ЦИФРОВОЙ ЭКОНОМИКОЙ","year":2025,"lang":"ru","type":"article","venue":"Экономика и предпринимательство","topic":"Agricultural Development and Policies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Order (exchange); Big data; Internet of Things; Key (lock); Digital transformation; Digital economy","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":[0.001671982,0.002933546,0.002833,0.0004864005,0.003157673,0.001914337,0.003982556,0.002154218,0.01131633],"category_scores_gemma":[0.0007387536,0.001505532,0.001818807,0.005760463,0.001366512,0.001735101,0.00207788,0.002257481,0.006163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008146384,"about_ca_system_score_gemma":0.0004907545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005532992,"about_ca_topic_score_gemma":0.004163712,"domain_scores_codex":[0.9857486,0.00094061,0.003375513,0.003391398,0.00213664,0.004407238],"domain_scores_gemma":[0.9934058,0.001499504,0.001343548,0.001185258,0.001179065,0.0013868],"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":[0.0006775327,0.001855976,0.03839865,0.000694095,0.001488812,0.0002599722,0.003443554,0.00008209488,0.03691832,0.02777419,0.6734762,0.2149306],"study_design_scores_gemma":[0.001730935,0.000712227,0.2251755,0.001068785,0.0005613806,0.00008396204,0.00293479,0.000196385,0.006204058,0.004294473,0.7538033,0.003234209],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7671964,0.01209605,0.00007974787,0.0433492,0.01082606,0.003598929,0.0009430003,0.001729884,0.1601808],"genre_scores_gemma":[0.7726032,0.004469365,0.0006167469,0.007415873,0.00382621,0.0003205494,0.001352769,0.00005202771,0.2093432],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2116964,"threshold_uncertainty_score":0.9991412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01036290283930294,"score_gpt":0.2195403355938937,"score_spread":0.2091774327545907,"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."}}