{"id":"W3183458655","doi":"10.32689/2617-2224-2019-4(19)-205-216","title":"ДЕРЖАВНІ ПЕРСПЕКТИВИ ФІНАНСОВОЇ ПІДТРИМКИ ВІДНОВЛЕННЯ ВНУТРІШНІХ ВОДНИХ ШЛЯХІВ ЗАДЛЯ ВКЛЮЧЕННЯ РІЧКОВОГО ТРАНСПОРТУ В СИСТЕМУ МУЛЬТИМОДАЛЬНИХ ПЕРЕВЕЗЕНЬ","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":"Political science","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":[0.003293474,0.001078526,0.0006047682,0.002618254,0.004609135,0.01337754,0.00157499,0.002968754,0.05512863],"category_scores_gemma":[0.009076674,0.0008154895,0.0009614139,0.002288422,0.007146415,0.007724591,0.004442954,0.004006619,0.01999701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005435423,"about_ca_system_score_gemma":0.009380857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0103752,"about_ca_topic_score_gemma":0.01030517,"domain_scores_codex":[0.9949971,0.001317857,0.0002778183,0.0008876938,0.001942813,0.0005767402],"domain_scores_gemma":[0.9960277,0.001008977,0.0003308031,0.0006802933,0.001492226,0.0004599747],"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":[0.00006366795,0.00005282745,0.001860466,0.0003062001,0.00003193665,0.0004334481,0.004402068,0.0009215319,0.001797206,0.9121867,0.02011118,0.05783277],"study_design_scores_gemma":[0.00003082608,0.00004938067,0.00353864,0.0004841224,0.00005159404,0.0005912046,0.005708452,0.001632157,0.002338034,0.3166812,0.6688052,0.00008921717],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02083597,0.006217142,0.07848628,0.01696723,0.001460839,0.0002371398,0.0008155228,0.0005327241,0.8744471],"genre_scores_gemma":[0.5222335,0.01164794,0.1036524,0.003862882,0.001029292,0.0008729727,0.001256521,0.001074629,0.3543698],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05512863,"threshold_uncertainty_score":0.1844236,"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."}}