{"id":"W7044282109","doi":"","title":"Workers’ compensation in Canada, and Colombia: A comparative analysis of non-pecuniary damages","year":2024,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Law, Economics, and Judicial Systems","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Damages; Compensation (psychology); Indemnity; Work (physics)","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":[0.0008714786,0.0004782526,0.0008822742,0.004448941,0.003256547,0.004704178,0.001764817,0.001093827,0.00640964],"category_scores_gemma":[0.004841318,0.0003779752,0.0008568411,0.009228163,0.001231362,0.0009443082,0.001375549,0.001263085,0.0003258553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06984274,"about_ca_system_score_gemma":0.04304325,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9957774,"about_ca_topic_score_gemma":0.9981285,"domain_scores_codex":[0.9984211,0.0001146883,0.00004732994,0.0001162699,0.0004315496,0.0008689981],"domain_scores_gemma":[0.9966099,0.0006298298,0.0004340129,0.00008303686,0.001530226,0.0007130287],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.001410104,0.0005113303,0.8475027,0.0009244874,0.0007450714,0.001778669,0.005484251,0.01044278,0.0009423922,0.02722565,0.03058061,0.07245199],"study_design_scores_gemma":[0.00007613839,0.00005198252,0.9653202,0.0001800319,0.0002550082,0.0001740649,0.01405384,0.001984498,0.0002769464,0.0005203214,0.01704433,0.00006259391],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9420847,0.01445429,0.0002427237,0.002579658,0.00006622592,0.0001435776,0.00655722,0.00003235353,0.03383909],"genre_scores_gemma":[0.9833398,0.004747988,0.0002108139,0.0002250872,0.0000190799,0.00002463153,0.003134272,0.00001317008,0.008285183],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06984274,"threshold_uncertainty_score":0.5067469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02296587766109623,"score_gpt":0.2286858533644309,"score_spread":0.2057199757033346,"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."}}