{"id":"W4408651941","doi":"10.34925/eip.2024.174.1.031","title":"NEW METHODOLOGICAL ASPECTS OF DIGITAL AGRICULTURAL MANAGEMENT BASED ON SPACE MONITORING DATA","year":2025,"lang":"ru","type":"article","venue":"Экономика и предпринимательство","topic":"Regional Socio-Economic Development Trends","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nordic Life Science Pipeline (Canada)","funders":"","keywords":"Agriculture; Space (punctuation); Computer science; Data science; Environmental resource management; Environmental science; Remote sensing; Geography; Archaeology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001790673,0.0006601643,0.0009983598,0.0003810492,0.0005401007,0.0004515421,0.002890017,0.0004620193,0.0005975874],"category_scores_gemma":[0.0007173866,0.0005800905,0.0003611042,0.001533554,0.0004728762,0.0007970463,0.001228642,0.0005407816,0.0003113085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008251115,"about_ca_system_score_gemma":0.0007840595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004993597,"about_ca_topic_score_gemma":0.00005694491,"domain_scores_codex":[0.9946875,0.0005207549,0.001056782,0.001541702,0.001156872,0.001036372],"domain_scores_gemma":[0.995741,0.001684787,0.0005827272,0.001431523,0.0001334082,0.0004265842],"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":[0.000513911,0.001275727,0.05015472,0.0005443246,0.002019977,0.0001617046,0.003198596,0.001100684,0.0001380383,0.470495,0.1990848,0.2713125],"study_design_scores_gemma":[0.004860425,0.0004385755,0.4680622,0.002277656,0.0008468813,0.000004311149,0.01899238,0.0006799176,0.001376926,0.02706017,0.4730265,0.002374069],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02712875,0.0009393923,0.006487092,0.02913951,0.006648123,0.001273898,0.0002144225,0.0003241646,0.9278446],"genre_scores_gemma":[0.8949191,0.0004723102,0.02619111,0.0002369805,0.0009966495,0.00002734102,0.0002023644,0.00004107112,0.07691307],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8677903,"threshold_uncertainty_score":0.9996651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1770187101478603,"score_gpt":0.3875639964771491,"score_spread":0.2105452863292888,"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."}}