{"id":"W4233705597","doi":"10.33423/jabe.v22i13.3911","title":"The More Income, the More Happiness. How Far?","year":2020,"lang":"en","type":"article","venue":"Journal of Applied Business and Economics","topic":"Psychological Well-being and Life Satisfaction","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Happiness; Per capita income; Ordinary least squares; Economics; Affect (linguistics); Estimation; Cluster (spacecraft); Demographic economics; Econometrics; Per capita; Psychology; Sociology; Demography; Social psychology; Computer science","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":[0.0003185336,0.0001423465,0.0002548152,0.0000308692,0.0002628936,0.0001661792,0.0002816487,0.000105736,0.00005057117],"category_scores_gemma":[0.00003001903,0.00007444779,0.00006947623,0.000143603,0.0001794254,0.00008412387,0.00005097481,0.0003397216,0.00002005978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001876644,"about_ca_system_score_gemma":0.00002175176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001160525,"about_ca_topic_score_gemma":0.000004444762,"domain_scores_codex":[0.999216,0.00002110138,0.0003440953,0.0001641263,0.00006487469,0.0001897588],"domain_scores_gemma":[0.9990686,0.000145093,0.0004398089,0.0001787809,0.00006947305,0.00009822736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.005091408,0.0002727318,0.02248742,0.0001208876,0.001392958,0.00008365118,0.01197199,0.00651071,0.000802171,0.223529,0.07648777,0.6512493],"study_design_scores_gemma":[0.001646279,0.0001005586,0.5214592,0.00001428733,0.00007727554,0.0001694061,0.007526152,0.0006889561,0.00002214871,0.005797595,0.4622332,0.0002650575],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8936127,0.0005708127,0.0008472869,0.08814819,0.001187676,0.0001481699,0.000005811299,0.00001835333,0.015461],"genre_scores_gemma":[0.9946602,0.0009695022,0.00007742821,0.00323527,0.0009300915,0.000007411903,0.000001361055,0.0000159157,0.0001027998],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6509843,"threshold_uncertainty_score":0.3035893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02343491837169437,"score_gpt":0.2540567978418273,"score_spread":0.2306218794701329,"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."}}