{"id":"W4388445281","doi":"10.5539/jpl.v16n4p36","title":"On the Illegality and Regulation of Algorithmic Price Discrimination in China's Digital Economy","year":2023,"lang":"en","type":"article","venue":"Journal of Politics and Law","topic":"Law, AI, and Intellectual Property","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tort; Price discrimination; Corporate governance; China; Big data; Monopoly; Law; Civil law (Civil law); Law and economics; Economics; Competition (biology); Political science; Public law; Market economy; Microeconomics; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005865558,0.0002299307,0.0002914651,0.002129822,0.004847164,0.005193966,0.001612368,0.003342359,0.003632352],"category_scores_gemma":[0.008178792,0.000315442,0.0006240511,0.001729976,0.01325972,0.003527289,0.002829995,0.003416724,0.0002573976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007536377,"about_ca_system_score_gemma":0.01383912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03986153,"about_ca_topic_score_gemma":0.0285144,"domain_scores_codex":[0.9941095,0.0009034259,0.000398224,0.001003577,0.002513756,0.00107151],"domain_scores_gemma":[0.9938246,0.002472841,0.001108459,0.001031818,0.001275055,0.0002872796],"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":[0.00001211333,0.00002278305,0.005496664,0.00003736283,0.000009028174,0.0003186732,0.001613045,0.0005574863,0.0005538233,0.974475,0.004270814,0.01263329],"study_design_scores_gemma":[0.0001027688,0.0001518105,0.06961036,0.0006092787,0.000187198,0.0009118287,0.002892982,0.02911103,0.00848272,0.6283956,0.2592507,0.0002937341],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.526264,0.003119454,0.01947457,0.03308931,0.0003220046,0.0002597621,0.0003965321,0.0001983771,0.416876],"genre_scores_gemma":[0.972225,0.000760958,0.002807789,0.005061255,0.0001219694,0.000111775,0.00007959017,0.00001980468,0.01881196],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03986153,"threshold_uncertainty_score":0.07925904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02511490172441169,"score_gpt":0.2466908780105292,"score_spread":0.2215759762861175,"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."}}