{"id":"W4292513552","doi":"10.1093/grurint/ikac076","title":"What’s Up, Latin America? Between Competition, Data and Consumer Protection","year":2022,"lang":"en","type":"article","venue":"GRUR International","topic":"European Criminal Justice and Data Protection","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Development Research Centre","keywords":"Enforcement; Latin Americans; Legislation; Position (finance); Competition (biology); Data Protection Act 1998; Business; Consumer protection; Privacy policy; Competition law; Action (physics); Law and economics; International trade; Information privacy; Political science; Economics; Law; Commerce; Market economy; Finance","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005247084,0.00005554353,0.00006129389,0.00007750608,0.0007038887,0.0002030006,0.0003941937,0.00001763265,0.001253634],"category_scores_gemma":[0.0002023728,0.00006368446,0.00001314199,0.0001203383,0.0001366976,0.0008392824,0.0004226784,0.0001833629,0.00007857022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007684692,"about_ca_system_score_gemma":0.00005301404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001480608,"about_ca_topic_score_gemma":0.0002027173,"domain_scores_codex":[0.9988619,0.0002232604,0.0001399749,0.0002442008,0.0004214002,0.000109239],"domain_scores_gemma":[0.9995449,0.00006599318,0.0000945915,0.0001734743,0.00007389252,0.00004715241],"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":[0.000282953,0.0002652974,0.02530946,0.000065135,0.0002928514,0.00003637893,0.03528447,0.00008627043,0.0008329405,0.07052754,0.07336729,0.7936494],"study_design_scores_gemma":[0.0001682287,0.00003576667,0.00574443,0.00001081831,0.00002340698,0.000004706,0.01472757,0.0004467501,0.00001160137,0.0006258919,0.978111,0.00008984814],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7409869,0.0009818261,0.06425887,0.09087543,0.03920706,0.00300566,0.004768703,0.0009040411,0.05501151],"genre_scores_gemma":[0.991505,0.0003527173,0.0003414803,0.0005377298,0.0008426578,0.00005009033,0.001115087,0.00001128996,0.005243948],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9047437,"threshold_uncertainty_score":0.9996594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1312287830290086,"score_gpt":0.3521184238782406,"score_spread":0.220889640849232,"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."}}