{"id":"W4249176856","doi":"10.32689/2617-2224-2019-17-2-124-135","title":"ДЕРЖАВНА ПОЛІТИКА ТА АКТИВІЗАЦІЯ ЇЇ ФУНКЦІЙ У РОЗВИТКУ ТВАРИННИЦТВА","year":2019,"lang":"uk","type":"article","venue":"UKRAINIAN ASSEMBLY OF DOCTORS OF SCIENCES IN PUBLIC ADMINISTRATION","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Tellabs (Canada)","funders":"","keywords":"Psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002874241,0.0008662125,0.0004802906,0.002024784,0.004344495,0.0126943,0.001080615,0.002306192,0.02778417],"category_scores_gemma":[0.006697862,0.0006523062,0.0008100438,0.001837639,0.01047278,0.007470176,0.00442846,0.003445567,0.01003446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005216658,"about_ca_system_score_gemma":0.0077508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007984278,"about_ca_topic_score_gemma":0.008254046,"domain_scores_codex":[0.9958514,0.001267535,0.0002216775,0.0007751035,0.00142069,0.0004636585],"domain_scores_gemma":[0.9970027,0.0008027928,0.0003011319,0.0004510525,0.001103825,0.0003385261],"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":[0.00003360902,0.00002593772,0.001370059,0.0001673681,0.00002174548,0.0002609342,0.006232702,0.0004357402,0.0009270987,0.9514701,0.008012701,0.03104187],"study_design_scores_gemma":[0.00002649863,0.00004921692,0.003611128,0.0004154183,0.00005069354,0.0005193767,0.009574346,0.000958016,0.001808423,0.4203365,0.5625764,0.00007391471],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02384892,0.006294027,0.06188317,0.01572653,0.0009596096,0.0001595763,0.0004923224,0.0002999032,0.890336],"genre_scores_gemma":[0.6763862,0.01010625,0.06376813,0.003427804,0.0007814415,0.0005613753,0.0006210088,0.0005502555,0.2437976],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02778417,"threshold_uncertainty_score":0.0929473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02263486865370148,"score_gpt":0.2783439392003582,"score_spread":0.2557090705466567,"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."}}