{"id":"W2991278454","doi":"10.1016/j.jeca.2019.e00139","title":"The impact of health on GDP: A panel data investigation","year":2019,"lang":"en","type":"article","venue":"The Journal of Economic Asymmetries","topic":"Global Health Care Issues","field":"Health Professions","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Life expectancy; Economics; Panel data; Granger causality; Econometrics; Demographic economics; Robustness (evolution); Cointegration; Per capita; Short run; Per capita income; Macroeconomics; Demography; Population","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":[0.005328937,0.0006320992,0.001179026,0.00152427,0.0009336513,0.002455559,0.001407614,0.001932224,0.008983939],"category_scores_gemma":[0.01022802,0.0006071595,0.001779214,0.003349096,0.0007554409,0.001230018,0.001977229,0.002679093,0.001282711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001046977,"about_ca_system_score_gemma":0.0008393107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03751273,"about_ca_topic_score_gemma":0.03200999,"domain_scores_codex":[0.9963073,0.002388525,0.0001507454,0.0003183576,0.0002492499,0.0005859216],"domain_scores_gemma":[0.9690112,0.02164639,0.005056103,0.001901292,0.001026137,0.001358909],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001560574,0.000881522,0.9491076,0.00015749,0.002402921,0.0008883884,0.0006679627,0.01908214,0.0005240187,0.003389517,0.01168554,0.009652222],"study_design_scores_gemma":[0.0001915779,0.0007949032,0.9575594,0.00009168727,0.001507603,0.0004304652,0.003810181,0.02339428,0.001071582,0.002233085,0.008813726,0.0001015248],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9767531,0.0007774175,0.001181935,0.001810335,0.00005943445,0.00005446038,0.01510396,0.00003435956,0.004225092],"genre_scores_gemma":[0.984211,0.0003799975,0.0002941137,0.0002647115,0.00006325742,0.0000420805,0.01234739,0.0000119758,0.002385495],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03751273,"threshold_uncertainty_score":0.07458872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2010978090719155,"score_gpt":0.4834919330335835,"score_spread":0.282394123961668,"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."}}