{"id":"W2107122082","doi":"10.1145/1135777.1135801","title":"Examining the content and privacy of web browsing incidental information","year":2006,"lang":"en","type":"article","venue":"","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Consistency (knowledge bases); World Wide Web; Information retrieval; Field (mathematics); Task (project management); Internet privacy; Partition (number theory); Scheme (mathematics); Information privacy; Artificial intelligence; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003498968,0.0001982392,0.0002644291,0.001153778,0.0006827621,0.001814578,0.0003048768,0.0005055621,0.001004645],"category_scores_gemma":[0.03546468,0.0002033393,0.0002302741,0.0007559737,0.0008288346,0.002013975,0.000741905,0.0004470181,0.0001653559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004314355,"about_ca_system_score_gemma":0.0003682535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001205535,"about_ca_topic_score_gemma":0.001766994,"domain_scores_codex":[0.9976074,0.001229095,0.0002250622,0.0002575544,0.0005306851,0.0001503372],"domain_scores_gemma":[0.9628072,0.02592137,0.005355569,0.002996579,0.002392143,0.0005271127],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001721454,0.0004488754,0.8283466,0.0004476295,0.0001516523,0.0004595861,0.05951847,0.0008128583,0.02670898,0.001650413,0.0002965362,0.07943694],"study_design_scores_gemma":[0.00003021292,0.0009984606,0.9442303,0.0001353151,0.0001346149,0.001285444,0.02536932,0.005322453,0.0143684,0.003688174,0.004356042,0.0000812764],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962315,0.00006380929,0.002192286,0.00003734582,0.000002923056,0.00002327297,0.00007034354,0.00001637667,0.001362095],"genre_scores_gemma":[0.9979589,0.00004659077,0.001573619,0.00001790865,0.000006822724,0.00001661102,0.0001135387,0.000007291476,0.0002587787],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003498968,"threshold_uncertainty_score":0.01850456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0521623647764124,"score_gpt":0.2767011611150725,"score_spread":0.2245387963386601,"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."}}