{"id":"W2109866768","doi":"10.34196/ijm.00024","title":"Scaling Up Infrastructure Spending in the Philippines: A CGE Top-Down Bottom-Up Microsimulation Approach","year":2009,"lang":"en","type":"article","venue":"","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computable general equilibrium; Microsimulation; Economics; Top-down and bottom-up design; Scaling; Macroeconomics; International economics; Regional science; Geography; Computer science; Engineering; Transport engineering","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":[0.0008423229,0.0009164608,0.001375827,0.0007854732,0.0006251849,0.001465718,0.001112241,0.00132138,0.005336307],"category_scores_gemma":[0.003309974,0.0005556921,0.001531864,0.0006757563,0.001048165,0.001206402,0.00161594,0.001345928,0.0002847044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001877414,"about_ca_system_score_gemma":0.001765083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05379121,"about_ca_topic_score_gemma":0.02114045,"domain_scores_codex":[0.9996575,0.0001442289,0.00001151089,0.0000656093,0.00003467544,0.00008642836],"domain_scores_gemma":[0.9987634,0.0007073534,0.0001625472,0.00006868531,0.0001897027,0.0001083942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002012161,0.00001522481,0.0007605752,0.00002276954,0.00003168499,0.00005792865,0.00002285489,0.9893734,0.0001184448,0.008154537,0.0002272374,0.001195211],"study_design_scores_gemma":[0.00001530899,0.00002005145,0.0003599778,0.000005765694,0.00002202812,0.000007804668,0.00003663118,0.9929178,0.00007272922,0.006097653,0.0004351616,0.00000902213],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5806612,0.001290682,0.3703145,0.004899933,0.0002078406,0.0002293994,0.001671773,0.0005747728,0.04014998],"genre_scores_gemma":[0.9739362,0.0005223458,0.01531071,0.0002992356,0.00004668684,0.0002373854,0.0003501279,0.00007017486,0.009227204],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05379121,"threshold_uncertainty_score":0.1069562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0312089011736325,"score_gpt":0.2372699954329254,"score_spread":0.2060610942592929,"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."}}