{"id":"W4407933134","doi":"10.33271/nvngu/2025-1/140","title":"The impact of educational development on the countries’ competitiveness in the knowledge economy","year":2025,"lang":"en","type":"article","venue":"Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu","topic":"Economic Issues in Ukraine","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ranking (information retrieval); Knowledge economy; Work (physics); Originality; Process (computing); Developing country; World economy; Questionnaire; Economy; Business; Economic growth; Economics; Political science; Engineering; Sociology; Computer science; Social science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00363649,0.0003840232,0.0003613109,0.003638278,0.0007611582,0.005258076,0.0004205646,0.0004365861,0.005372072],"category_scores_gemma":[0.01047042,0.0000975695,0.0005932995,0.003797489,0.001011497,0.001807041,0.001994345,0.000717207,0.0003847749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00284913,"about_ca_system_score_gemma":0.00628686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006923849,"about_ca_topic_score_gemma":0.007684309,"domain_scores_codex":[0.9962305,0.001532153,0.0002194655,0.0002132452,0.001064918,0.0007396979],"domain_scores_gemma":[0.9909237,0.003150495,0.001265998,0.0003371015,0.003469759,0.0008530433],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003239743,0.0002669327,0.4230101,0.005035979,0.0006325493,0.001243108,0.003804138,0.01063746,0.002021686,0.1477655,0.01470791,0.3905506],"study_design_scores_gemma":[0.00003112988,0.0005064695,0.796539,0.004540754,0.0006565999,0.0006669192,0.02532596,0.005020212,0.004725083,0.0272788,0.1346015,0.000107543],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6122493,0.01820916,0.009850904,0.01130076,0.0006586257,0.0004111039,0.002290659,0.0001083078,0.3449211],"genre_scores_gemma":[0.9918183,0.003974119,0.001916146,0.0002099012,0.00005909423,0.00004381366,0.0002932023,0.000008405703,0.001677058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006923849,"threshold_uncertainty_score":0.02067202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01857021866238387,"score_gpt":0.2821268313538576,"score_spread":0.2635566126914737,"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."}}