{"id":"W4220862099","doi":"10.1109/cdma54072.2022.00032","title":"Legal Judgment Prediction for Canadian Appeal Cases","year":2022,"lang":"en","type":"article","venue":"","topic":"Artificial Intelligence in Law","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Appeal; Computer science; Task (project management); Binary classification; Artificial intelligence; Natural language processing; Legal case; Focus (optics); Domain (mathematical analysis); Data science; Law; Political science; Support vector machine; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005134595,0.00004191171,0.00004811937,0.00005692961,0.002322799,0.00005264485,0.0001558349,0.00002410709,0.003869578],"category_scores_gemma":[0.000107303,0.00004646691,0.00004009966,0.0001454915,0.00009743254,0.0001217178,0.00002373507,0.00006394763,0.00003264828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000612978,"about_ca_system_score_gemma":0.0006270397,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8596464,"about_ca_topic_score_gemma":0.9271485,"domain_scores_codex":[0.9991405,0.00006551028,0.0001145852,0.0001342698,0.0002442153,0.0003008947],"domain_scores_gemma":[0.999607,0.00008753516,0.00002180132,0.00007443363,0.00004300628,0.0001661927],"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":[0.00001331533,0.00002977172,0.001305762,0.000001479674,0.000007548036,0.00001127343,0.003916317,0.0005737165,0.0000374768,0.9102383,0.07579388,0.008071203],"study_design_scores_gemma":[0.0000194879,0.00008172108,0.0000582256,6.232785e-7,0.000004515954,0.000002099699,0.01662047,0.0004957996,0.0001554688,0.001982749,0.9805203,0.00005850197],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1424454,0.00005854909,0.003238835,0.0223153,0.004913193,0.001842327,0.0004304895,0.0003081528,0.8244478],"genre_scores_gemma":[0.9862787,0.00000238633,0.0001811755,0.0007253097,0.0003255636,0.0001783092,0.0000139564,0.000005757567,0.0122888],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9082555,"threshold_uncertainty_score":0.9989761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07721048625188753,"score_gpt":0.3467467586953007,"score_spread":0.2695362724434132,"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."}}