{"id":"W2517464265","doi":"10.1007/978-3-319-42644-0_3","title":"Data Publishing: Trading Off Privacy with Utility Through the k-Jump Strategy","year":2016,"lang":"en","type":"book-chapter","venue":"Advances in information security","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Generalization; Computer science; Jump; Data publishing; Algorithm; k-anonymity; Function (biology); Order (exchange); sort; Data mining; Property (philosophy); Information privacy; Computer security; Publishing; Mathematics; Database","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":[0.003811089,0.000672145,0.0016047,0.00105463,0.001609782,0.006292773,0.003014475,0.003422136,0.01063731],"category_scores_gemma":[0.02075457,0.0005355536,0.001109168,0.002841456,0.005854458,0.01621465,0.004448967,0.006499939,0.002013387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002089602,"about_ca_system_score_gemma":0.001636433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006711892,"about_ca_topic_score_gemma":0.0004686818,"domain_scores_codex":[0.997144,0.001044686,0.0001849725,0.000457435,0.0008882557,0.0002805872],"domain_scores_gemma":[0.9879616,0.008249757,0.000418669,0.002508132,0.0004633947,0.000398382],"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":[0.0001525577,0.0000391279,0.0002095715,0.00008710725,0.00002377395,0.00008957857,0.0001575075,0.007679721,0.000724701,0.940297,0.00372111,0.04681819],"study_design_scores_gemma":[0.00002258007,0.0000244409,0.00004062131,0.00002766521,0.000009781514,0.00009704907,0.00002778395,0.04465915,0.000835525,0.9503477,0.0038923,0.00001538869],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04902142,0.004577735,0.850874,0.01175832,0.000730821,0.0001374042,0.0003036462,0.001050841,0.08154572],"genre_scores_gemma":[0.8269411,0.003313986,0.1254237,0.001236164,0.0008406402,0.0001800215,0.0001938925,0.000552049,0.04131846],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01063731,"threshold_uncertainty_score":0.03558534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05886952337423467,"score_gpt":0.2996862859546866,"score_spread":0.2408167625804519,"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."}}