{"id":"W7000662142","doi":"","title":"A frolic in the law of tort: expanding
\\nthe scope of employers' vicarious
\\nliability","year":2010,"lang":"en","type":"article","venue":"The HKU Scholars Hub (University of Hong Kong)","topic":"Discrimination and Equality Law","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vicarious liability; Scope (computer science); Liability; Supreme court; Context (archaeology); Strict liability; Connection (principal bundle); Common law","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":[0.003655097,0.0001114714,0.0002850976,0.00009988215,0.0005978727,0.00004512344,0.001374008,0.0001458739,0.0004088533],"category_scores_gemma":[0.0003077268,0.00008997184,0.0001725415,0.0005496959,0.002018559,0.0006111471,0.0001624361,0.0004521303,0.00001698863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003963577,"about_ca_system_score_gemma":0.0001409193,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.04835096,"about_ca_topic_score_gemma":0.1670298,"domain_scores_codex":[0.9979441,0.0007002266,0.0002346171,0.000209137,0.0006554484,0.0002565325],"domain_scores_gemma":[0.9985489,0.0003465315,0.0002606834,0.000566995,0.0002024483,0.0000744844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002411226,0.0008672503,0.1212677,0.0001103302,0.00009993881,0.000008814914,0.3515426,0.00003340011,0.008484614,0.5132514,0.0008321198,0.003260744],"study_design_scores_gemma":[0.001652985,0.000170278,0.8031045,0.0001286412,0.0001701256,0.000001460973,0.1551346,0.00002757446,0.001698078,0.02538573,0.01214978,0.0003762708],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9299045,0.00002198753,0.00002363915,0.002742156,0.0001759196,0.0003051809,0.00002320783,0.0000225097,0.06678092],"genre_scores_gemma":[0.9992663,0.00003667171,0.0001449595,0.0001300059,0.00002991347,5.359117e-7,0.000003010975,0.000006179184,0.0003824131],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6818368,"threshold_uncertainty_score":0.9579862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02294656041733631,"score_gpt":0.29260061939094,"score_spread":0.2696540589736037,"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."}}