{"id":"W3107524348","doi":"","title":"Monopolization Remedies and Data Privacy","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Intellectual Property Law","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Douglas College","funders":"","keywords":"Monopolization; Internet privacy; Business; Consumer privacy; Information privacy; Competition (biology); Privacy laws of the United States; Personally identifiable information; Liability; FTC Fair Information Practice; Privacy by Design; Privacy policy; Law and economics; Law; Information privacy law; Economics; Political science; Computer science; Monopoly; Finance","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02336347,0.0006433192,0.001039758,0.003117712,0.008221645,0.01343396,0.00398475,0.01738963,0.008256814],"category_scores_gemma":[0.0494043,0.001059725,0.002085831,0.002342886,0.03166637,0.01878234,0.009570905,0.0151405,0.001799057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009325406,"about_ca_system_score_gemma":0.01316256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006435291,"about_ca_topic_score_gemma":0.004897221,"domain_scores_codex":[0.9479684,0.01583275,0.002935907,0.006835966,0.02143665,0.004990299],"domain_scores_gemma":[0.9377645,0.03795234,0.00665166,0.01121404,0.005079543,0.001337992],"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":[0.000007767247,0.00002171821,0.000391541,0.00003899463,0.000008246362,0.0001959283,0.0006598201,0.000277708,0.0001888044,0.9892358,0.002933456,0.006040275],"study_design_scores_gemma":[0.00004058279,0.0001018293,0.001423329,0.0007666464,0.00005178954,0.0008751437,0.001089813,0.002326428,0.001757965,0.8359362,0.1555429,0.00008744291],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0592142,0.01242438,0.1167798,0.1542703,0.001014245,0.0003699251,0.0003298816,0.0003936984,0.6552036],"genre_scores_gemma":[0.8871234,0.004073061,0.023053,0.04538713,0.0009562336,0.0004363876,0.000176116,0.0001241859,0.03867046],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02336347,"threshold_uncertainty_score":0.1235593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0784044117464456,"score_gpt":0.3301102745561783,"score_spread":0.2517058628097327,"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."}}