{"id":"W7099625373","doi":"","title":"Disabled Workers and Earnings Losses: Some Evidence from Workers with Occupational Injuries","year":2004,"lang":"en","type":"article","venue":"","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Earnings; Wage; Matching (statistics); Work (physics); Hourly wage; Persistence (discontinuity)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002521006,0.0002047982,0.0003596461,0.002094219,0.000677639,0.0008880185,0.0006892919,0.0007401765,0.005295356],"category_scores_gemma":[0.02039587,0.000193316,0.0004489143,0.002352294,0.001317456,0.0006867631,0.001840301,0.0007478587,0.0004110611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003645037,"about_ca_system_score_gemma":0.0004109475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0202934,"about_ca_topic_score_gemma":0.01968691,"domain_scores_codex":[0.9986401,0.0004845616,0.0001361887,0.0001307328,0.0003673537,0.0002409741],"domain_scores_gemma":[0.965297,0.01633903,0.0136878,0.001849024,0.001533619,0.001293546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003892347,0.00008288186,0.9887154,0.00005326424,0.00009533267,0.0001361075,0.0003860823,0.000135295,0.00005367651,0.0001881742,0.000165977,0.009598592],"study_design_scores_gemma":[0.00001022088,0.000105886,0.9981813,0.00003271336,0.00006523926,0.0001562409,0.0006113207,0.0001005136,0.00008400143,0.0001618344,0.0004862385,0.000004608312],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946364,0.002103135,0.0001393854,0.0006856473,0.000005385317,0.00000784641,0.0003998386,0.000002946529,0.002019473],"genre_scores_gemma":[0.9983096,0.0009403823,0.00004489617,0.00007723855,0.00001977317,0.000002583111,0.0002452093,0.000001544781,0.0003586522],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0202934,"threshold_uncertainty_score":0.04035062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01704938844790826,"score_gpt":0.2389760104503476,"score_spread":0.2219266220024393,"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."}}