{"id":"W2034944813","doi":"10.5539/ass.v5n2p93","title":"Research on the Efficiency of China’s Anti-monopoly Law","year":2009,"lang":"en","type":"article","venue":"Asian Social Science","topic":"Merger and Competition Analysis","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Monopoly; China; Argument (complex analysis); Enforcement; State (computer science); Economics; Law and economics; Law; Market economy; Microeconomics; Business; Political 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":[0.006841827,0.0002706631,0.00062256,0.002439544,0.001020649,0.003270793,0.000973894,0.001121924,0.00492081],"category_scores_gemma":[0.01593494,0.0002650862,0.0005247356,0.002185608,0.004021239,0.003857239,0.0009827431,0.001337713,0.0002252251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005129497,"about_ca_system_score_gemma":0.004568771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01687698,"about_ca_topic_score_gemma":0.008446454,"domain_scores_codex":[0.9968201,0.001047525,0.0001574959,0.0004014857,0.001078423,0.0004950423],"domain_scores_gemma":[0.9839289,0.007481435,0.003758798,0.001138191,0.003354139,0.0003385399],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00006290746,0.00009709108,0.04259837,0.0002416377,0.0001863352,0.0002474598,0.0007157171,0.009113722,0.001077806,0.8989502,0.002531539,0.04417728],"study_design_scores_gemma":[0.0002008659,0.0003566658,0.2566086,0.0004138931,0.0005190961,0.0004200891,0.002757484,0.1335045,0.005700452,0.5636055,0.03578226,0.0001305745],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8108475,0.005326412,0.01655636,0.008430731,0.00009611489,0.0001181061,0.0001465317,0.00005243983,0.1584258],"genre_scores_gemma":[0.9953467,0.001139876,0.0005717449,0.0001712125,0.00007200367,0.0000138672,0.00003916154,0.000005317348,0.002640102],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01687698,"threshold_uncertainty_score":0.03721732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05103770805067125,"score_gpt":0.3150427220242837,"score_spread":0.2640050139736124,"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."}}