{"id":"W4401720461","doi":"10.1109/re59067.2024.00012","title":"AI-Enabled Regulatory Change Analysis of Legal Requirements","year":2024,"lang":"en","type":"article","venue":"","topic":"Artificial Intelligence in Law","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds National de la Recherche Luxembourg; Science Foundation Ireland","keywords":"Computer science; Risk analysis (engineering); Business","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008883101,0.00006989924,0.0001759032,0.0003063378,0.000159963,0.0000995844,0.000223381,0.00007425511,0.003855184],"category_scores_gemma":[0.00007675726,0.00006287708,0.000167806,0.00194807,0.000322949,0.0005890288,0.00003994634,0.00006994608,0.0001838348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001052266,"about_ca_system_score_gemma":0.0001125049,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01377328,"about_ca_topic_score_gemma":0.01549363,"domain_scores_codex":[0.9986917,0.00009414247,0.0002623385,0.0002177761,0.000488458,0.0002456335],"domain_scores_gemma":[0.9994916,0.00008508103,0.00003807334,0.0001994962,0.0001088929,0.00007686745],"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":[0.000005241401,0.0000335716,0.002254172,0.00001299951,0.0004390961,0.00000936767,0.008687872,0.00002690026,0.0005315832,0.9696348,0.004266681,0.0140977],"study_design_scores_gemma":[0.00003200458,0.00006017758,0.002835253,0.00007297551,0.001121076,1.875262e-7,0.008201378,0.01140777,0.01007299,0.01131446,0.9545343,0.0003474265],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3918249,0.0009963554,0.003662829,0.01159733,0.002430037,0.0006458227,0.00002154514,0.0006292585,0.5881919],"genre_scores_gemma":[0.9868261,0.00003807753,0.0001117513,0.00044031,0.0002439112,0.00001392244,0.000003376998,0.000007235504,0.01231529],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9583204,"threshold_uncertainty_score":0.9970554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1347408663952767,"score_gpt":0.4260631045154787,"score_spread":0.2913222381202021,"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."}}