{"id":"W2587304703","doi":"","title":"The Evolution of Consumer Privacy Law: How Privacy by Design Can Benefit from Insights in Commercial Law and Standardization","year":2012,"lang":"en","type":"article","venue":"eYLS (Yale Law School)","topic":"Legal Systems and Judicial Processes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Scope (computer science); Personally identifiable information; Privacy by Design; Business; Consumer protection; Temptation; Standardization; Transferability; Information privacy; Information privacy law; Limiting; Internet privacy; Privacy policy; FTC Fair Information Practice; Law and economics; Law; Computer science; Economics; Political science; Incentive; Microeconomics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008097821,0.0001403673,0.0002585539,0.0000247039,0.001006249,0.0002367103,0.0002665087,0.0001616183,0.00002079789],"category_scores_gemma":[0.0002640735,0.0001116823,0.00003588075,0.0002449847,0.0005759866,0.0008661692,0.00007492214,0.000177887,0.000006149451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002885735,"about_ca_system_score_gemma":0.0001789188,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3497345,"about_ca_topic_score_gemma":0.1964297,"domain_scores_codex":[0.9982597,0.0003931304,0.0002931894,0.0002038659,0.000474474,0.0003757009],"domain_scores_gemma":[0.9989094,0.0003224621,0.0002015331,0.0002058822,0.0001659422,0.0001947796],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000667395,0.0000758904,0.02313134,0.00001988931,0.0000324371,6.26366e-7,0.01046886,0.00001075925,0.0008966656,0.9626629,0.001965479,0.0006683446],"study_design_scores_gemma":[0.001157083,0.00007821395,0.0109436,0.0001607347,0.00005352472,4.85371e-7,0.003040489,0.00001544016,0.003808736,0.05379052,0.9265559,0.0003953253],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9359947,0.02714297,0.002755969,0.003692642,0.001054947,0.001498994,0.0001783911,0.000110567,0.02757077],"genre_scores_gemma":[0.9987737,0.0002717518,0.0001447383,0.0002667787,0.0003741538,0.00001765124,0.00001240406,0.00001465178,0.0001241865],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9245903,"threshold_uncertainty_score":0.8182333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01959248869254737,"score_gpt":0.2636593672511173,"score_spread":0.24406687855857,"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."}}