{"id":"W80674782","doi":"10.1163/ej.9789004155633.i-342.69","title":"Chapter 13. Awarding Damages for Distress and Loss of Reputation in England and Canada","year":2007,"lang":"en","type":"book-chapter","venue":"","topic":"Legal principles and applications","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Damages; Reputation; Underpinning; Distress; Test (biology); Political science; Law; Law and economics; Economics; Psychology; Engineering","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":[0.002274354,0.0006171592,0.0004825148,0.002367083,0.01625212,0.009453108,0.002157711,0.005078695,0.01537453],"category_scores_gemma":[0.004633908,0.0003903967,0.0004886318,0.003191911,0.008206243,0.001813019,0.001642224,0.004575477,0.001214508],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1490132,"about_ca_system_score_gemma":0.1143659,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9869671,"about_ca_topic_score_gemma":0.9945596,"domain_scores_codex":[0.9959217,0.0002598585,0.0001205748,0.0002708058,0.002638347,0.000788554],"domain_scores_gemma":[0.9982824,0.0004423693,0.00005583282,0.00004560116,0.001010997,0.0001628824],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000009965563,0.00001090236,0.0004032792,0.0001219652,0.000005238897,0.0002726713,0.005304647,0.0003704773,0.0001729402,0.7443877,0.230635,0.0183052],"study_design_scores_gemma":[0.000005105786,0.000006067401,0.002125081,0.0003115344,0.00001071421,0.0001070438,0.003168964,0.0001861237,0.0001693719,0.01744732,0.9764147,0.00004807921],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.008810755,0.03720124,0.00111822,0.04680214,0.002548985,0.0001250007,0.0005796762,0.00007884998,0.9027352],"genre_scores_gemma":[0.1394071,0.02176332,0.001437084,0.01420796,0.0005527142,0.00006183126,0.0001965957,0.00008011853,0.8222933],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1490132,"threshold_uncertainty_score":0.9870241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03126637737145373,"score_gpt":0.3005026928216856,"score_spread":0.2692363154502319,"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."}}