{"id":"W2954705643","doi":"10.1007/s10657-019-09623-8","title":"Compensation in personal injury cases: mean or median income?","year":2019,"lang":"en","type":"article","venue":"European Journal of Law and Economics","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Thornhill Medical (Canada)","funders":"","keywords":"Compensation (psychology); Economics; Work (physics); Adjusted gross income; Median income; Personal injury; Personal income; Demographic economics; Gross income; Actuarial science; Econometrics; Medicine; Public economics; Psychology; Population; Environmental health; Law; Economic growth; State income tax; Social psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006139319,0.0002809236,0.001511194,0.00358245,0.0007645335,0.003018097,0.001573583,0.002115302,0.01076839],"category_scores_gemma":[0.04027779,0.000390235,0.0007932701,0.002850906,0.001771404,0.004311123,0.002132742,0.001763058,0.00081395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009988048,"about_ca_system_score_gemma":0.0009803352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002537867,"about_ca_topic_score_gemma":0.00347794,"domain_scores_codex":[0.9959711,0.001359392,0.0003905988,0.000451656,0.000600601,0.00122652],"domain_scores_gemma":[0.9690459,0.01665703,0.008665945,0.0009020925,0.00199413,0.002734992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001029107,0.0003216765,0.9121633,0.000173149,0.0003926868,0.0009176666,0.000755854,0.003561953,0.0001167736,0.02813038,0.01906035,0.03337725],"study_design_scores_gemma":[0.000102502,0.0003693057,0.8761064,0.0005891314,0.0003274795,0.002587812,0.008241924,0.01363891,0.0002932396,0.09244,0.005183649,0.0001196755],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9457111,0.007081063,0.002713213,0.01908373,0.000379638,0.00004396958,0.002139317,0.0000509739,0.02279695],"genre_scores_gemma":[0.9983374,0.0003643132,0.0001065709,0.0002081247,0.0003165655,0.000008960323,0.0002704902,0.000004238272,0.000383303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01076839,"threshold_uncertainty_score":0.03602386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05609629027654071,"score_gpt":0.2546096133548635,"score_spread":0.1985133230783228,"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."}}