{"id":"W4366352052","doi":"10.1002/hec.4687","title":"Childhood‐onset disabilities and lifetime earnings growth: A longitudinal analysis","year":2023,"lang":"en","type":"article","venue":"Health Economics","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Earnings; Earnings growth; Demographic economics; Economics; Demography; Longitudinal data; Finance","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001700019,0.0001236382,0.0003409386,0.000155686,0.0007854319,0.0001195041,0.0001518139,0.00006607054,0.0002536251],"category_scores_gemma":[0.0003598831,0.0001338461,0.0001250901,0.0004645165,0.0004296153,0.0001563644,0.0000805224,0.0001026108,0.0001539516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003044871,"about_ca_system_score_gemma":0.0002929601,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01259492,"about_ca_topic_score_gemma":0.01235437,"domain_scores_codex":[0.998354,0.0001953032,0.0003853039,0.0004034818,0.0001206247,0.0005412831],"domain_scores_gemma":[0.9989476,0.0003421233,0.0001346518,0.000211325,0.00002993754,0.0003343908],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000006010909,0.00004647009,0.9593813,0.0000403075,0.00008489402,1.929105e-7,0.03317717,0.0000510354,2.826773e-8,0.004462266,0.001740879,0.001009408],"study_design_scores_gemma":[0.00014986,0.00007189122,0.9728176,0.000008314345,0.00004669538,3.196499e-7,0.01062813,0.0002363216,5.296001e-7,0.005379496,0.01050485,0.000155978],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9800568,0.0001002958,0.000006111224,0.01667338,0.0001853576,0.0003115284,0.00004281837,0.0001366518,0.002487036],"genre_scores_gemma":[0.9950227,0.003281223,0.00005789725,0.0004960894,0.0001822537,0.00003954257,0.00004139797,0.00001216438,0.0008667258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02254903,"threshold_uncertainty_score":0.9939803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1555390152612058,"score_gpt":0.4036726915495172,"score_spread":0.2481336762883115,"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."}}