{"id":"W2155075220","doi":"10.2139/ssrn.1505311","title":"Growth, Development and Natural Resources: New Evidence Using a Heterogeneous Panel Analysis","year":2011,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Natural Resources and Economic Development","field":"Economics, Econometrics and Finance","cited_by":54,"is_retracted":false,"has_abstract":false,"ca_institutions":"Trinity College","funders":"","keywords":"Econometrics; Economics; Panel data; Robustness (evolution); Estimation; Inference; Value (mathematics); Statistics; Computer science; Mathematics","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":[0.005949219,0.0006618094,0.001333558,0.001639501,0.0009260733,0.001855389,0.00122448,0.001182807,0.007482893],"category_scores_gemma":[0.0118854,0.0005014995,0.001473443,0.004379179,0.0009493686,0.001457727,0.001820326,0.001689674,0.0009721729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004631147,"about_ca_system_score_gemma":0.0004369975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02363048,"about_ca_topic_score_gemma":0.02896808,"domain_scores_codex":[0.9969321,0.001846505,0.0001962432,0.0005180968,0.0002721426,0.00023482],"domain_scores_gemma":[0.9368981,0.04816342,0.007658214,0.005150391,0.001013352,0.001116537],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002972813,0.001232485,0.8827531,0.0005349122,0.00948771,0.001138955,0.001145815,0.02708347,0.001232206,0.008337003,0.01165768,0.05242399],"study_design_scores_gemma":[0.0006632323,0.0006209605,0.9360211,0.0002487634,0.007183453,0.0004256974,0.002524468,0.02351379,0.001593849,0.01412432,0.01292356,0.0001567698],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9764364,0.004239646,0.00823184,0.000926363,0.00008063042,0.00004105596,0.006169737,0.00004340813,0.003830886],"genre_scores_gemma":[0.985797,0.001895716,0.001779454,0.0002534933,0.0001523458,0.00004340793,0.008763527,0.00001783245,0.001297222],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02363048,"threshold_uncertainty_score":0.04698586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07254467373381872,"score_gpt":0.2227518040978971,"score_spread":0.1502071303640784,"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."}}