{"id":"W4410162614","doi":"10.18280/ijsdp.200419","title":"The Nexus Among Human Capital, Monetary Policy, and Regional Economic Growth: Comparison of the West and East Region Indonesia","year":2025,"lang":"en","type":"article","venue":"International Journal of Sustainable Development and Planning","topic":"Economic Growth and Fiscal Policies","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nexus (standard); Human capital; Economics; Monetary policy; Economic geography; Capital (architecture); Development economics; Geography; Economy; Economic growth; Macroeconomics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0002924563,0.0001240941,0.0002121556,0.0005032128,0.0001906546,0.0009059643,0.0001703356,0.00009730181,0.000980288],"category_scores_gemma":[0.0006156367,0.00008109382,0.0002309577,0.0008447345,0.0002375512,0.0005675653,0.0005010515,0.0003388486,0.0001461641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000649901,"about_ca_system_score_gemma":0.0006492476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02611201,"about_ca_topic_score_gemma":0.02969865,"domain_scores_codex":[0.9998537,0.00003231137,0.00001264304,0.00002752381,0.00002312758,0.00005062649],"domain_scores_gemma":[0.9995984,0.0001083641,0.0001379259,0.00001986145,0.00006278371,0.00007264503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001786256,0.00009530342,0.9788185,0.00005263526,0.0001015838,0.0005636537,0.0009696131,0.002756456,0.0006424952,0.001997799,0.000629014,0.01319422],"study_design_scores_gemma":[0.000005166791,0.00002644841,0.990846,0.0000255719,0.00005185275,0.0001479457,0.002942297,0.003934522,0.0003937781,0.0003552022,0.00126378,0.000007408946],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950752,0.0002034327,0.0001625919,0.0001831478,0.000004531556,0.000003780725,0.0002469594,0.000002910217,0.004117452],"genre_scores_gemma":[0.9992466,0.0001578286,0.00007547291,0.00001448331,0.000002248024,0.000003055102,0.0001357834,0.000001001299,0.0003635933],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02611201,"threshold_uncertainty_score":0.05192006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02271029466878633,"score_gpt":0.2464653944541151,"score_spread":0.2237550997853288,"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."}}