{"id":"W2756235250","doi":"10.15353/rea.v9i2.1437","title":"Business ‘Psych’cles: A Close Look at Mental Health and State-level Economic Performance Using Google Search Data","year":2017,"lang":"en","type":"article","venue":"Review of Economic Analysis","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Otago","keywords":"Misfortune; Mental health; State (computer science); Public health; The Internet; Psychology; Mental state; Business; Psychiatry; Demographic economics; Economics; Medicine; Computer science; World Wide Web; Nursing","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":[0.00139863,0.0002822767,0.0006485475,0.01722808,0.0004977142,0.002254906,0.0004100218,0.0005869343,0.00370949],"category_scores_gemma":[0.01021068,0.0001533002,0.001018251,0.03216239,0.0002930645,0.002254843,0.001358031,0.0005567025,0.001344484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007332877,"about_ca_system_score_gemma":0.001019692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0695968,"about_ca_topic_score_gemma":0.1140451,"domain_scores_codex":[0.9984439,0.0004294697,0.0002664007,0.0001653694,0.0005138276,0.0001811103],"domain_scores_gemma":[0.9922438,0.003606363,0.002206218,0.0003997021,0.001190883,0.0003529712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002021454,0.00008722734,0.8448305,0.00292301,0.0008248951,0.0004435648,0.002110158,0.0008755579,0.0004063315,0.003773878,0.09697036,0.04655243],"study_design_scores_gemma":[0.00001125251,0.00004379459,0.9376042,0.0005301129,0.0001473392,0.0003550233,0.004496685,0.001464661,0.0001553128,0.0006382594,0.05450868,0.00004475207],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6153334,0.01700848,0.00118954,0.005085593,0.0002099406,0.0001600534,0.3367394,0.0002494092,0.02402418],"genre_scores_gemma":[0.8072378,0.008088541,0.003053987,0.0006873118,0.0002717615,0.0001846846,0.1771156,0.0001300288,0.003230287],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0695968,"threshold_uncertainty_score":0.1383834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1883661793154107,"score_gpt":0.4518651026429806,"score_spread":0.2634989233275699,"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."}}