{"id":"W4253273889","doi":"10.4018/978-1-60566-982-3.ch104","title":"Privacy Concerns for Web Logging Data","year":2011,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"HIV, Drug Use, Sexual Risk","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Internet privacy; Logging; Data collection; Information privacy; Web application; Safeguarding; Key (lock); Computer security; World Wide Web; Data science; Geography","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":[0.03802609,0.0005639851,0.0007098287,0.001995163,0.004213188,0.01333012,0.00244552,0.004428237,0.007843341],"category_scores_gemma":[0.06098744,0.0007597317,0.0007426013,0.003420046,0.005477354,0.01727081,0.004643831,0.006443174,0.003109919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002394477,"about_ca_system_score_gemma":0.003826648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001538798,"about_ca_topic_score_gemma":0.001990733,"domain_scores_codex":[0.956156,0.02630952,0.002429541,0.001652609,0.01268099,0.0007712954],"domain_scores_gemma":[0.8304965,0.1408132,0.004993822,0.01431871,0.008415443,0.0009623468],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001445481,0.0001721645,0.004434596,0.001648901,0.00003541957,0.001640531,0.03237966,0.001502313,0.003253495,0.473823,0.06348235,0.417483],"study_design_scores_gemma":[0.00002211384,0.0001218596,0.001910445,0.003270031,0.00004122966,0.005347573,0.009151184,0.002724238,0.005903109,0.174073,0.7973296,0.0001057775],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.03528469,0.03625718,0.4475278,0.1199453,0.003360018,0.001576402,0.001146934,0.002346739,0.3525551],"genre_scores_gemma":[0.3960051,0.04844014,0.3130322,0.0501195,0.004955814,0.004084196,0.002042101,0.00200134,0.1793196],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.03802609,"threshold_uncertainty_score":0.2011036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1623498300236595,"score_gpt":0.3729483489996593,"score_spread":0.2105985189759998,"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."}}