{"id":"W2144326136","doi":"10.1016/j.datak.2008.12.001","title":"Privacy-preserving data publishing for cluster analysis","year":2008,"lang":"en","type":"article","venue":"Data & Knowledge Engineering","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":71,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ontario Institute of Technology; Simon Fraser University; Concordia University","funders":"","keywords":"Masking (illustration); Data publishing; Computer science; Cluster (spacecraft); ENCODE; Data mining; Process (computing); Publishing; Focus (optics); Data anonymization; Class (philosophy); Data quality; Information retrieval; Information privacy; Artificial intelligence; Computer security; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006926941,0.0005263381,0.001854571,0.001792489,0.002728708,0.005056927,0.003076259,0.001532212,0.002324322],"category_scores_gemma":[0.03288099,0.0008451137,0.00159527,0.005332273,0.002297281,0.007467228,0.005082353,0.003182583,0.001305502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001503709,"about_ca_system_score_gemma":0.003811897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001013557,"about_ca_topic_score_gemma":0.001051106,"domain_scores_codex":[0.9911855,0.002892425,0.0008234037,0.001312297,0.003109221,0.0006770661],"domain_scores_gemma":[0.9556216,0.01076213,0.001690366,0.02847267,0.002801351,0.0006518385],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001338456,0.0003639558,0.006240323,0.000412576,0.0003559277,0.0005107038,0.001313812,0.1009111,0.01305623,0.5428522,0.01780894,0.3148358],"study_design_scores_gemma":[0.00008015711,0.0001250941,0.0007616991,0.00005221397,0.0001186501,0.0008378302,0.0003644412,0.338026,0.03172371,0.6112437,0.01661352,0.00005301265],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01765741,0.0004554803,0.976899,0.001134892,0.0001432694,0.0001020426,0.0006301852,0.0008840122,0.002093802],"genre_scores_gemma":[0.6327802,0.0009427636,0.3554146,0.0005749061,0.000479353,0.0003063797,0.001963372,0.0003865457,0.007151898],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006926941,"threshold_uncertainty_score":0.03663361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1037152150446969,"score_gpt":0.306164189747526,"score_spread":0.2024489747028291,"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."}}