{"id":"W2134369111","doi":"","title":"The Effects of Cancer on Employment and Earnings of Cancer Survivors","year":2014,"lang":"en","type":"article","venue":"Analytical Studies Branch Research Paper Series","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Microdata (statistics); Earnings; Demography; Cancer registry; Wage; Cancer; Matching (statistics); Medicine; Propensity score matching; Causal inference; Econometrics; Actuarial science; Demographic economics; Economics; Census; Environmental health; Labour economics; Surgery; Population; Accounting; Internal medicine; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001310519,0.0001794856,0.0005247413,0.00007661666,0.0003152196,0.00002036602,0.0002406095,0.00006518265,0.00002775302],"category_scores_gemma":[0.00762553,0.0001059629,0.00006818622,0.0003388058,0.001776582,0.0001162843,0.0003205539,0.0003500381,0.000001446748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007249274,"about_ca_system_score_gemma":0.00003460048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001066361,"about_ca_topic_score_gemma":0.009450192,"domain_scores_codex":[0.9977583,0.000361895,0.0003724117,0.0002737355,0.0007661111,0.0004674923],"domain_scores_gemma":[0.989511,0.009299255,0.0001177981,0.0003657948,0.0006223435,0.00008379722],"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":[0.0007025341,0.0003108116,0.09830317,0.003895553,0.001997287,0.000006279495,0.005189426,0.00001542293,0.01232594,0.7370126,0.004066979,0.1361739],"study_design_scores_gemma":[0.001189024,0.005136074,0.1564841,0.002877343,0.0002909767,0.000001305079,0.00314863,0.0001544513,0.1479479,0.6180268,0.06401241,0.0007309862],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9839152,0.0100697,0.0001927437,0.003246615,0.0001010505,0.0006846337,0.000006685237,0.00007207429,0.001711327],"genre_scores_gemma":[0.9675621,0.030247,0.0002739201,0.00006264259,0.00006270743,0.0003463319,2.828344e-7,0.00002585138,0.001419116],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1356219,"threshold_uncertainty_score":0.9129022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1594103281262531,"score_gpt":0.503943175039,"score_spread":0.3445328469127469,"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."}}