{"id":"W1767010817","doi":"","title":"'The Melancholy Truth': Corrective and Equitable Justice for Omar Khadr","year":2014,"lang":"en","type":"article","venue":"Dalhousie journal of legal studies","topic":"Criminal Law and Evidence","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Injustice; Context (archaeology); Economic Justice; Harm; Law; Constructive trust; Sociology; Appeal; Order (exchange); Proposition; Government (linguistics); Principal (computer security); Faith; Repatriation; Law and economics; Remedial education; Political science; Economics; Philosophy; History; Theology; Epistemology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.01012671,0.0002756902,0.0005377836,0.0008325462,0.02481911,0.01122031,0.001377136,0.01054179,0.003433469],"category_scores_gemma":[0.01443667,0.0003135686,0.0003249993,0.0006291386,0.02629399,0.003997139,0.00519254,0.01113184,0.0003660889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01789955,"about_ca_system_score_gemma":0.03197239,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2528425,"about_ca_topic_score_gemma":0.4193631,"domain_scores_codex":[0.9914186,0.002706632,0.0003586963,0.0006243159,0.00261159,0.002280178],"domain_scores_gemma":[0.9946035,0.002390121,0.0005728155,0.0004147489,0.001414757,0.0006041083],"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":[0.00005178536,0.00005501609,0.001849775,0.0001191872,0.00002021749,0.001042489,0.02412248,0.0002864867,0.0006669508,0.9198889,0.03323752,0.01865901],"study_design_scores_gemma":[0.00009110674,0.0001298333,0.01171292,0.0009412895,0.0001080849,0.001509425,0.0946144,0.001117273,0.002773931,0.3471257,0.5395694,0.0003066344],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1349662,0.01406092,0.004083205,0.6162264,0.002455362,0.0001409193,0.00008925116,0.00009243342,0.2278853],"genre_scores_gemma":[0.9399727,0.001539579,0.001835661,0.04198379,0.0003457532,0.00001793914,0.00001204437,0.00002018896,0.01427242],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7471576,"threshold_uncertainty_score":0.5027415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05605805057015369,"score_gpt":0.3831973261374007,"score_spread":0.327139275567247,"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."}}