{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009448988,0.0001339084,0.0004889273,0.0001402605,0.0005272262,0.00001339694,0.001036427,0.00007987733,0.00009846476],"category_scores_gemma":[0.0008482062,0.00006566493,0.00009181628,0.0001644584,0.0001484472,0.000281292,0.000208985,0.0006315786,0.0005280524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007582441,"about_ca_system_score_gemma":0.00233517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003316193,"about_ca_topic_score_gemma":0.0003747299,"domain_scores_codex":[0.9965439,0.001319002,0.001432359,0.0001147273,0.0001933428,0.0003966443],"domain_scores_gemma":[0.991789,0.004253997,0.002728478,0.0009154414,0.0001741902,0.0001389115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001762223,0.0000667489,0.2610959,0.0003105897,0.000467883,9.469871e-7,0.01152028,0.001696447,0.00005098897,0.01139627,0.6992008,0.01243088],"study_design_scores_gemma":[0.002940215,0.004354653,0.8839105,0.001443126,0.00007881696,0.00004044978,0.03001832,0.001527779,0.0001289458,0.01680765,0.05844911,0.0003003865],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9824737,0.002865059,0.00001351804,0.0103281,0.001425405,0.0005594778,0.0001296748,0.000008522805,0.002196586],"genre_scores_gemma":[0.9970464,0.001381749,0.00006108613,0.0006984182,0.0003086416,0.000001236964,0.000009222839,0.00001673273,0.0004765676],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6407517,"threshold_uncertainty_score":0.6787221,"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."}}