{"id":"W2975640247","doi":"10.21083/surg.v11i0.5354","title":"Estimating the Financial Return to Education Between Fields of Study","year":2019,"lang":"en","type":"article","venue":"SURG Journal","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Regression analysis; Rate of return; Population; Scope (computer science); Regression; Actuarial science; Econometrics; Demographic economics; Term (time); Relation (database); Expected return; Economics; Finance; Statistics; Demography; Mathematics; Computer science; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.006306172,0.0005987335,0.0006832301,0.003621844,0.0009796988,0.001931907,0.001487389,0.0006335624,0.006288141],"category_scores_gemma":[0.02915732,0.0003413,0.001366621,0.003287449,0.0005632165,0.001072151,0.001700313,0.001292275,0.0009956331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007855406,"about_ca_system_score_gemma":0.0117613,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5706576,"about_ca_topic_score_gemma":0.5896358,"domain_scores_codex":[0.9971417,0.0005546254,0.0002195209,0.0004398655,0.0008673579,0.0007768497],"domain_scores_gemma":[0.9922169,0.002874871,0.001503655,0.0003446203,0.002332479,0.0007273415],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001160607,0.00007860228,0.9636452,0.00005716044,0.0001945104,0.0000904108,0.0007087535,0.002185626,0.0001090739,0.002298501,0.00234438,0.02817166],"study_design_scores_gemma":[0.00001950692,0.0001473729,0.9786985,0.00008965748,0.0001488909,0.00009150589,0.001799025,0.01102262,0.0002336647,0.001177848,0.006541746,0.00002956643],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9703354,0.0005598229,0.008731786,0.001049179,0.00006936194,0.0004811403,0.009815112,0.0001196835,0.008838488],"genre_scores_gemma":[0.9752677,0.0003244366,0.008173808,0.0001375038,0.00002502144,0.0004284355,0.006738208,0.00002541887,0.008879548],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5706576,"threshold_uncertainty_score":0.8637419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01337461813111958,"score_gpt":0.258958963706474,"score_spread":0.2455843455753544,"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."}}