{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.0605868,0.001012141,0.001217269,0.01077118,0.003137327,0.01896497,0.002561455,0.004044886,0.02747232],"category_scores_gemma":[0.3316505,0.001632179,0.0007239742,0.01048257,0.001906336,0.02140349,0.005173738,0.007729454,0.01660083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002637594,"about_ca_system_score_gemma":0.01205817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002414251,"about_ca_topic_score_gemma":0.002222014,"domain_scores_codex":[0.9453218,0.02613704,0.009390964,0.002844966,0.0148765,0.001428692],"domain_scores_gemma":[0.4133088,0.2987607,0.0334099,0.1948678,0.05421312,0.005439679],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001346841,0.001105712,0.02820873,0.000972647,0.0001191498,0.0009773343,0.008486343,0.005739233,0.006987454,0.103028,0.3853627,0.4576659],"study_design_scores_gemma":[0.0004629465,0.000467252,0.01068022,0.001752658,0.0001585279,0.0008820373,0.006589294,0.07958946,0.04429215,0.1851015,0.6695782,0.0004457377],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08538182,0.0009048578,0.565567,0.06798815,0.009747937,0.003963979,0.0418079,0.09769134,0.1269471],"genre_scores_gemma":[0.5846655,0.001304362,0.295889,0.005878203,0.004187137,0.001952257,0.03736132,0.01069512,0.05806721],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9974385,"threshold_uncertainty_score":0.3204174,"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."}}