{"id":"W7107867321","doi":"10.5281/zenodo.17734133","title":"THE ROLE OF ARTIFICIAL INTELLIGENCE (AI) IN CONSUMER PROTECTION ACT IN PRESENT PROSPECTIVE","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Law, AI, and Intellectual Property","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Consumer protection; Product liability; Agency (philosophy); Government (linguistics); Liability; Data Protection Act 1998; Corporate governance; Product (mathematics); Consumer Bill of Rights; Consumer privacy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007537206,0.00008341514,0.0001043132,0.000223918,0.0006159145,0.0004367956,0.001162107,0.00004289294,0.0002605839],"category_scores_gemma":[0.0007995347,0.00006521823,0.00002828564,0.001171356,0.0002303197,0.0003016422,0.0009206359,0.0002733732,0.0003994671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001530824,"about_ca_system_score_gemma":0.00001468497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001110422,"about_ca_topic_score_gemma":0.00000936731,"domain_scores_codex":[0.9985741,0.0003482919,0.0002978109,0.0003138888,0.0002231692,0.00024277],"domain_scores_gemma":[0.999127,0.00004840134,0.00006148406,0.000375313,0.0003516128,0.00003618322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001411923,0.0002289994,0.00003138933,0.00002557962,0.00001804079,0.000002464026,0.003083884,0.0001536542,0.008427188,0.1153141,0.003332197,0.8692412],"study_design_scores_gemma":[0.0002517276,0.0004023949,0.001827247,0.0001075319,0.000004091878,0.00001372584,0.0008750084,0.1426522,0.06964059,0.04894413,0.7350675,0.0002138454],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03992561,0.001094077,0.5760353,0.008023017,0.0006261089,0.005302609,0.00002436959,0.0009852701,0.3679836],"genre_scores_gemma":[0.9993344,0.00006819105,0.0001245316,0.0000435106,0.00002080543,3.009254e-7,0.00000608857,0.00008954572,0.000312649],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9594088,"threshold_uncertainty_score":0.5134475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03170233842086166,"score_gpt":0.2534721400234139,"score_spread":0.2217698016025523,"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."}}