{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003507211,0.0001032322,0.0002318725,0.0003332898,0.0003014414,0.0001483501,0.0002466134,0.00005572371,0.000001450496],"category_scores_gemma":[0.00006710034,0.00008165942,0.00003977559,0.00006250566,0.0002069814,0.0002621102,0.0001547094,0.0001584117,4.372541e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000130588,"about_ca_system_score_gemma":0.00009789362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004329392,"about_ca_topic_score_gemma":0.00003380718,"domain_scores_codex":[0.9990212,0.00001365006,0.0006417484,0.0001177124,0.00004136569,0.0001643238],"domain_scores_gemma":[0.9991097,0.0001099741,0.0005821114,0.00005838014,0.00009005446,0.00004972624],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000335013,0.0000101568,0.7542133,0.00002024498,0.0001079609,0.000008210875,0.003768451,0.00006324417,0.000001409354,0.2409571,0.0005129244,0.0003034486],"study_design_scores_gemma":[0.0004935183,0.00002127684,0.950546,0.00007425174,0.000005982097,0.00003238624,0.01056678,0.0002042112,0.00003471177,0.03345289,0.00447744,0.00009058148],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990699,0.003470624,0.00008295383,0.00288083,0.0002137386,0.00007424843,0.000003227075,0.00000252017,0.002572892],"genre_scores_gemma":[0.9990135,0.0001623762,0.00003116183,0.0001371706,0.0001195424,0.000002579598,0.000002632334,0.000005377868,0.0005256257],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2075042,"threshold_uncertainty_score":0.3329974,"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."}}