{"id":"W2133733758","doi":"10.1109/cisda.2009.5356544","title":"Secure two and multi-party association rule mining","year":2009,"lang":"en","type":"article","venue":"","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Ontario Centres of Excellence","keywords":"Computer science; Association rule learning; Cardinality (data modeling); Intersection (aeronautics); Protocol (science); Computer security; Data mining; Set (abstract data type); Product (mathematics); Raw data; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0002924291,0.00007980867,0.00009027036,0.00005497946,0.00008073595,0.0001516462,0.004730651,0.00007912011,0.000009675396],"category_scores_gemma":[0.007105949,0.00007161385,0.00001548374,0.0002080504,0.00001291422,0.000608263,0.01297376,0.0001137098,0.00002367953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006328998,"about_ca_system_score_gemma":0.00001409953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003117229,"about_ca_topic_score_gemma":0.00003376155,"domain_scores_codex":[0.9991906,0.00002581812,0.0001137572,0.0002910875,0.0001584302,0.0002203066],"domain_scores_gemma":[0.9976019,0.0001105137,0.00006992038,0.002150314,0.00003265264,0.00003468931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002714921,0.0001309503,0.0373489,0.000008029306,0.00002949051,0.00002259439,0.0004999781,0.00000792276,0.00274261,0.0187136,0.7117087,0.2287845],"study_design_scores_gemma":[0.0008892374,0.00007709565,0.03715876,0.00002214808,0.000006187676,0.00001573496,0.00005344868,0.7671687,0.006843106,0.1828183,0.004602919,0.0003443776],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2013611,0.0001889618,0.6818791,0.1035576,0.0003379271,0.0001886982,0.000006882509,0.002210903,0.01026877],"genre_scores_gemma":[0.300688,0.00001263794,0.6983442,0.0005434633,0.00001576001,0.000001814551,0.000002301603,0.000002293853,0.000389566],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7671608,"threshold_uncertainty_score":0.9950091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0269744405882696,"score_gpt":0.2874892600448015,"score_spread":0.2605148194565319,"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."}}