{"id":"W1486289494","doi":"","title":"Privacy-Preserving Data Mining in Electronic Surveys","year":2007,"lang":"en","type":"article","venue":"Journal of the Association for Information Systems","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Randomized response; Computer science; Data mining; Information privacy; Scheme (mathematics); Classifier (UML); Naive Bayes classifier; Information sensitivity; Machine learning; Artificial intelligence; Computer security; Support vector machine; Statistics; Mathematics","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":[0.05005558,0.0008118632,0.002562902,0.001734641,0.003032442,0.004029287,0.004393742,0.003423535,0.001577886],"category_scores_gemma":[0.1138453,0.001315162,0.002182291,0.003724854,0.005022868,0.01015818,0.007365079,0.004102529,0.001203046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002243064,"about_ca_system_score_gemma":0.004401573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007990458,"about_ca_topic_score_gemma":0.0005890967,"domain_scores_codex":[0.8891079,0.08516993,0.0044521,0.007458489,0.01156051,0.002251035],"domain_scores_gemma":[0.8663952,0.05883771,0.01288287,0.05601911,0.004565171,0.001299943],"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":[0.002770862,0.000727628,0.01425854,0.0006145234,0.0003667557,0.0005931382,0.003487906,0.07728951,0.01221057,0.5466436,0.006129419,0.3349077],"study_design_scores_gemma":[0.000569331,0.0006329148,0.002501664,0.0001804021,0.0001241131,0.0009384103,0.0005616812,0.3747623,0.02185968,0.5859123,0.01180938,0.0001478459],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02733396,0.0002080072,0.9680508,0.001814607,0.00004477004,0.0003543918,0.0001754616,0.0005540488,0.001464039],"genre_scores_gemma":[0.5477455,0.0003213493,0.44732,0.0008158309,0.0001759127,0.001144487,0.0003601785,0.00006470473,0.002052003],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05005558,"threshold_uncertainty_score":0.2647223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03765736113327567,"score_gpt":0.2931612768465376,"score_spread":0.2555039157132619,"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."}}