{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001567083,0.00128408,0.0006792519,0.00467643,0.001976109,0.001987252,0.001750443,0.001281299,0.00961056],"category_scores_gemma":[0.00876938,0.0002584279,0.001058764,0.002465648,0.0007001541,0.0008184427,0.001249314,0.001729819,0.002541348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01860201,"about_ca_system_score_gemma":0.01750374,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.912695,"about_ca_topic_score_gemma":0.9277802,"domain_scores_codex":[0.9986849,0.000122045,0.00005924323,0.0002522398,0.0005597785,0.0003217457],"domain_scores_gemma":[0.9967648,0.0009608315,0.0001502653,0.0001643923,0.00155636,0.000403278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001275572,0.001315506,0.220827,0.0006379404,0.0003746869,0.002664974,0.0007424421,0.1434201,0.002672459,0.008949785,0.2161159,0.4010039],"study_design_scores_gemma":[0.0001437786,0.0001170161,0.1304049,0.0001629,0.0001402312,0.0003337494,0.001041919,0.8278544,0.003337804,0.004100046,0.0322635,0.00009976462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8999081,0.002989171,0.01120188,0.004856434,0.0005028061,0.0005160337,0.03376012,0.003057719,0.04320766],"genre_scores_gemma":[0.9246924,0.0007352643,0.009989933,0.0003504035,0.0001121066,0.00007690593,0.0489646,0.00007375686,0.01500453],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08730501,"threshold_uncertainty_score":0.1756383,"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."}}