{"id":"W3098702500","doi":"10.3386/w24596","title":"Does Investment in National Highways Help or Hurt Hinterland City Growth?","year":2018,"lang":"en","type":"preprint","venue":"National Bureau of Economic Research","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Department for International Development; University of Oxford; International Growth Centre; World Bank Group","keywords":"Investment (military); Agriculture; Population; Business; Population growth; Economic geography; Economics; Geography","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":[0.0008005251,0.0002690499,0.0002650427,0.0006997225,0.000424668,0.00155837,0.0004235981,0.0007187157,0.003826508],"category_scores_gemma":[0.00331327,0.00009924619,0.0003862066,0.0008275541,0.0009113416,0.00116881,0.0008391876,0.0007129007,0.0003217947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002103207,"about_ca_system_score_gemma":0.001552557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05947415,"about_ca_topic_score_gemma":0.08192791,"domain_scores_codex":[0.9997388,0.00006432232,0.000009715369,0.00003213586,0.00002558668,0.0001293926],"domain_scores_gemma":[0.9973917,0.0005311896,0.001236174,0.00007867737,0.0002477835,0.0005144519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002693488,0.0001530714,0.9547156,0.0001195423,0.000170372,0.0004762512,0.0006379528,0.003211754,0.0003695632,0.01090374,0.005261198,0.02371149],"study_design_scores_gemma":[0.00005416999,0.0001695007,0.9663185,0.0001208459,0.0003050666,0.00007382168,0.008068111,0.008113973,0.0009785051,0.005726355,0.0100461,0.00002511221],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9820686,0.00140769,0.0001936169,0.008551462,0.00005663064,0.000008637237,0.0005025489,0.00001630317,0.007194525],"genre_scores_gemma":[0.9977847,0.0007064031,0.00006255772,0.000267568,0.00003527685,0.000002999132,0.0001507036,0.00000253429,0.0009872416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05947415,"threshold_uncertainty_score":0.1182559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3337442817504104,"score_gpt":0.4317937894019768,"score_spread":0.09804950765156645,"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."}}