{"id":"W7010858879","doi":"","title":"Judging the Social Sciences in Carter v. Canada","year":2016,"lang":"en","type":"article","venue":"eYLS (Yale Law School)","topic":"Diverse Interdisciplinary Research Studies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Supreme court; Scrutiny; Adversarial system; Expert witness; Charter; Witness; Economic Justice; Criminal justice","routes":{"ca_aff":false,"ca_fund":true,"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":[0.0006160963,0.0001131091,0.0001340316,0.00005415417,0.0008356882,0.0002330831,0.001599857,0.00002310165,0.00006902201],"category_scores_gemma":[0.00008102853,0.00005940511,0.00004328832,0.0003968637,0.0004268212,0.00065556,0.001167505,0.0001437683,0.0001101971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002721001,"about_ca_system_score_gemma":0.0004416505,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1495054,"about_ca_topic_score_gemma":0.6663446,"domain_scores_codex":[0.9981947,0.0001175826,0.0001608948,0.0003597658,0.0006431981,0.0005238845],"domain_scores_gemma":[0.9993635,0.0001853493,0.00004148322,0.0002899879,0.00006160553,0.00005808864],"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":[0.00002005716,0.000092112,0.1037327,0.00002491816,0.00008301914,0.0004110039,0.003772656,0.00003789966,0.001694778,0.5561897,0.3090568,0.02488428],"study_design_scores_gemma":[0.003099135,0.000431747,0.4397752,0.0005087717,0.0000169399,0.00005538624,0.003596955,0.002453248,0.003627395,0.04157611,0.5030906,0.001768523],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6998073,0.0003242625,0.002574877,0.1786637,0.00203993,0.0005461706,0.00003441745,0.0001915473,0.1158178],"genre_scores_gemma":[0.9970108,0.000005310927,0.0002280935,0.001206342,0.0001358424,0.000023356,1.124301e-7,0.000003957176,0.001386212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5168392,"threshold_uncertainty_score":0.8561581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02839948542203991,"score_gpt":0.2954557472222958,"score_spread":0.2670562618002559,"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."}}