{"id":"W3125101722","doi":"10.2139/ssrn.3180340","title":"Publishing Privacy Logs to Facilitate Transparency and Accountability","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; McMaster University","funders":"","keywords":"Computer science; Accountability; Privacy policy; Audit; Transparency (behavior); Information privacy; SPARQL; Implementation; Computer security; World Wide Web; Internet privacy; Semantic Web; Accounting; Business; RDF; Software engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.02373188,0.0001506234,0.0002401472,0.0002628734,0.0004295419,0.001857722,0.001490604,0.00006006904,0.0002965266],"category_scores_gemma":[0.003465325,0.000111478,0.00007980099,0.0006273825,0.0001583521,0.002993731,0.0002953822,0.0009323081,0.0003292518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003426439,"about_ca_system_score_gemma":0.0006546989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003527181,"about_ca_topic_score_gemma":0.006173926,"domain_scores_codex":[0.9955087,0.0003208475,0.0006960157,0.0005354946,0.001186443,0.001752553],"domain_scores_gemma":[0.9983035,0.0003180642,0.0001714427,0.0006154607,0.0003625479,0.0002290351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001928125,0.0001208446,0.008104032,0.000008248497,0.00009514273,0.000002757039,0.008763948,0.000007567171,0.0001750587,0.1890115,0.01603822,0.7774799],"study_design_scores_gemma":[0.000376215,0.0003919503,0.009960795,0.000008428085,0.00001316675,0.00004715589,0.006864547,0.0000349906,0.00002600916,0.751771,0.2303455,0.0001602136],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7517141,0.0005022434,0.2208049,0.01953217,0.0005370876,0.0002843004,0.0000397635,0.00004458041,0.006540806],"genre_scores_gemma":[0.9955245,0.0002702975,0.0004367823,0.0009582939,0.0002366343,0.000004287455,0.000002913082,0.000007447962,0.002558801],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7773197,"threshold_uncertainty_score":0.9991785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1979379976863958,"score_gpt":0.3898169333303212,"score_spread":0.1918789356439254,"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."}}