{"id":"W4389571075","doi":"10.3233/faia230995","title":"OpenJustice.ai: A Global Open-Source Legal Language Model","year":2023,"lang":"en","type":"book-chapter","venue":"Frontiers in artificial intelligence and applications","topic":"Artificial Intelligence in Law","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Misinformation; Transparency (behavior); Computer science; Narrative; Economic Justice; Political science; Law; Internet privacy; Computer security; Linguistics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009298995,0.000419027,0.0005849775,0.0002368072,0.000975772,0.0007987387,0.001693046,0.0005944953,0.0002215558],"category_scores_gemma":[0.0001707487,0.0004915083,0.0001355108,0.000478351,0.001496174,0.0005019375,0.0005732028,0.0006681568,0.0008173018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004079967,"about_ca_system_score_gemma":0.0006103489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003599648,"about_ca_topic_score_gemma":0.01546188,"domain_scores_codex":[0.9968102,0.00006799892,0.0009110626,0.0009889987,0.0005468419,0.0006749089],"domain_scores_gemma":[0.9984259,0.0001490455,0.0002812645,0.0006408797,0.0001935256,0.0003093654],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002314153,0.00004416014,0.00001958225,0.00001391504,0.00002247853,0.000009791964,0.001762944,0.00192627,0.000003405641,0.7677711,0.004995608,0.2234076],"study_design_scores_gemma":[0.00001300211,0.00002014742,9.067798e-7,0.00009716202,0.00005815181,0.000001151235,0.007917831,0.01428237,0.00005099286,0.6574916,0.3195887,0.0004780306],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00002252057,0.000484108,0.4959674,0.001878145,0.0006047832,0.002063503,0.0002479334,0.0002028958,0.4985287],"genre_scores_gemma":[0.03443384,0.004084356,0.01483105,0.001888581,0.002167762,0.001390983,0.0002354221,0.0002555313,0.9407125],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4811364,"threshold_uncertainty_score":0.9999607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08520170282171409,"score_gpt":0.3817058505167751,"score_spread":0.296504147695061,"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."}}