{"id":"W4318711953","doi":"10.2139/ssrn.4325813","title":"Adult Income Prediction Using various ML Algorithms","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lambton College","funders":"","keywords":"Algorithm; Computer science; Econometrics; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.004578047,0.000161945,0.000187143,0.0004106742,0.001428482,0.0001806875,0.0004295946,0.0001696532,0.0000349707],"category_scores_gemma":[0.0001113794,0.0001636669,0.0001780704,0.00134432,0.0001676741,0.0004261358,0.00006468765,0.001638928,0.0001018341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001474989,"about_ca_system_score_gemma":0.001416443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003474279,"about_ca_topic_score_gemma":0.008429589,"domain_scores_codex":[0.9954205,0.0002997155,0.0003758133,0.0002721813,0.0009124058,0.00271935],"domain_scores_gemma":[0.9992167,0.00003703501,0.000210023,0.0001901022,0.0002129343,0.0001331912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005749056,0.0001886324,0.1954135,0.00002892899,0.0008142478,0.00008206639,0.007145402,0.001818152,0.0001149321,0.7032952,0.0008482237,0.09019319],"study_design_scores_gemma":[0.001960586,0.0004742499,0.1274111,0.0001115345,0.0002993858,0.0001742162,0.03066415,0.01037987,0.00002013165,0.8001068,0.0275285,0.0008695248],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9711707,0.0008652211,0.01335844,0.001816048,0.002857681,0.0004946809,0.00001411995,0.0005478943,0.008875193],"genre_scores_gemma":[0.9859416,0.01084779,0.000212505,0.0001037035,0.001314457,0.000009942969,0.000005912607,0.00003127784,0.001532799],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0968116,"threshold_uncertainty_score":0.9998716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01554085379103332,"score_gpt":0.2991394890255707,"score_spread":0.2835986352345374,"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."}}