{"id":"W3035938238","doi":"","title":"Is There A Long Run Nexus Among Mental Disorder And Socio-Economic Indicators? : Experiences From An Econometric Study Across 40 Countries","year":2020,"lang":"en","type":"article","venue":"Regional Science Inquiry","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cointegration; Nexus (standard); Economics; Per capita; Poverty; Granger causality; Causality (physics); Per capita income; Mental health; Development economics; Globalization; Demographic economics; Econometrics; Economic growth; Psychology; Demography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00276439,0.0002183103,0.0003936443,0.00115098,0.0004456494,0.001068716,0.000365685,0.000379424,0.0009867958],"category_scores_gemma":[0.004903186,0.0002552343,0.000678417,0.003781308,0.0009997269,0.0006607805,0.001342367,0.0005910289,0.0001949456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008340922,"about_ca_system_score_gemma":0.0005222437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04196861,"about_ca_topic_score_gemma":0.03293704,"domain_scores_codex":[0.9988035,0.0007091474,0.00008719812,0.0001045259,0.00009012377,0.0002054942],"domain_scores_gemma":[0.9949747,0.003071696,0.001127415,0.0002836604,0.0003084042,0.0002341311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006140531,0.00007431659,0.9918103,0.00003370816,0.000123192,0.0003920921,0.002244779,0.001103744,0.00008127166,0.0003536231,0.000247445,0.003474165],"study_design_scores_gemma":[0.000006067909,0.00009186177,0.9861848,0.00003086277,0.00009812443,0.000152796,0.01071044,0.001593957,0.00008859985,0.000157817,0.0008708574,0.00001388194],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987665,0.0002031197,0.0002479095,0.0001350622,0.000002519183,0.000006690743,0.0002372987,0.000001845115,0.0003991288],"genre_scores_gemma":[0.9991184,0.0002267822,0.0001113216,0.00003877374,0.000005529857,0.000009324415,0.0003643428,0.000001631528,0.0001238213],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04196861,"threshold_uncertainty_score":0.08344865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1063752776909264,"score_gpt":0.4394686531348376,"score_spread":0.3330933754439113,"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."}}