{"id":"W7101107903","doi":"","title":"Data Transformation For Privacy-Preserving Data Mining","year":2008,"lang":"en","type":"article","venue":"","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Permission; Association rule learning; Association (psychology); Data association; Context (archaeology); Data collection","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00482024,0.0004397455,0.0008388198,0.001640595,0.0008536116,0.002747252,0.001476053,0.0007358852,0.002769987],"category_scores_gemma":[0.01368152,0.0005123451,0.001608626,0.00305745,0.001575931,0.003591559,0.003649904,0.002068278,0.002058161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007784799,"about_ca_system_score_gemma":0.001715043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007613671,"about_ca_topic_score_gemma":0.000635531,"domain_scores_codex":[0.9933805,0.002248274,0.000726139,0.001008848,0.002318337,0.0003178244],"domain_scores_gemma":[0.9905651,0.002569489,0.0004342659,0.005407978,0.0008996984,0.0001235303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009926658,0.0004458854,0.005462526,0.0004884062,0.0002403355,0.0006614515,0.0007784601,0.05405323,0.02001061,0.2122575,0.02157093,0.683038],"study_design_scores_gemma":[0.00008411516,0.0002003259,0.001075476,0.00008525568,0.00006688254,0.001237018,0.0003472146,0.4668767,0.05712166,0.4271444,0.04571635,0.0000444759],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01078114,0.0003529469,0.9824725,0.0006958276,0.00007824269,0.0001974599,0.0006701624,0.002316588,0.002435177],"genre_scores_gemma":[0.4031223,0.0007516958,0.5854683,0.000568017,0.0001625063,0.0004253889,0.003901298,0.0004979289,0.005102526],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00482024,"threshold_uncertainty_score":0.02549219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1978914207527445,"score_gpt":0.3380490661056479,"score_spread":0.1401576453529034,"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."}}