{"id":"W4388469709","doi":"10.2139/ssrn.4597917","title":"JudicialTech supporting Justice","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Dispute Resolution and Class Actions","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Economic Justice; Political science; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.003758567,0.0005586487,0.0008207463,0.001790256,0.01184703,0.01646874,0.001981203,0.01945472,0.1842469],"category_scores_gemma":[0.01787437,0.0006609361,0.0006274343,0.001232833,0.002611305,0.004180296,0.004490927,0.01188287,0.05159139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004042694,"about_ca_system_score_gemma":0.009468206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01103087,"about_ca_topic_score_gemma":0.0378454,"domain_scores_codex":[0.9956338,0.0007146605,0.0001821807,0.0007167714,0.001613358,0.001139253],"domain_scores_gemma":[0.9936871,0.002828499,0.0002499859,0.0008067796,0.001353358,0.001074313],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003058851,0.00005441739,0.0002599525,0.00006739359,0.00000669622,0.00019595,0.0002293764,0.0000509993,0.0002007891,0.2058782,0.7701709,0.0228547],"study_design_scores_gemma":[0.00002370753,0.00001648591,0.0004986186,0.0001368328,0.00001077732,0.00005359579,0.0003251655,0.0001380956,0.0003086523,0.03063429,0.9678419,0.00001192808],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.00243538,0.004348039,0.0004729107,0.09294953,0.008007972,0.0000466581,0.0003614162,0.0002301405,0.8911479],"genre_scores_gemma":[0.04983668,0.002108321,0.0004704977,0.04822459,0.004407151,0.00007653431,0.00025534,0.0001837457,0.8944373],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1842469,"threshold_uncertainty_score":0.6163671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01553103434655501,"score_gpt":0.2697904852370098,"score_spread":0.2542594508904548,"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."}}