{"id":"W74281023","doi":"","title":"Specifying Personal Privacy Policies to Avoid Unexpected Outcomes.","year":2005,"lang":"en","type":"article","venue":"NPARC","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Research Council Canada","keywords":"Internet privacy; Computer science; Information privacy; Computer security; Privacy software; Privacy policy; Personally identifiable information; Business","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05750225,0.001194786,0.0008693972,0.001870907,0.004497287,0.007753016,0.004069376,0.007362771,0.005847349],"category_scores_gemma":[0.1107747,0.001498638,0.002357992,0.001422123,0.007265625,0.01403844,0.008106411,0.01148542,0.002400696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003210013,"about_ca_system_score_gemma":0.01084336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004568869,"about_ca_topic_score_gemma":0.004211348,"domain_scores_codex":[0.939435,0.03209686,0.006211156,0.004117903,0.01494466,0.003194407],"domain_scores_gemma":[0.8580941,0.08180003,0.007797618,0.03905866,0.01149603,0.001753544],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009096126,0.0001640443,0.002705808,0.0003191289,0.0001015315,0.0009242718,0.005004379,0.005938117,0.002990435,0.9182537,0.01516087,0.04834677],"study_design_scores_gemma":[0.000108286,0.0001195799,0.0008203593,0.0007344447,0.0001952603,0.002142423,0.001854408,0.02842957,0.01466455,0.7346172,0.2161489,0.0001651547],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01041311,0.0006003414,0.9208596,0.0135943,0.0004363724,0.001095878,0.000576471,0.002021919,0.05040213],"genre_scores_gemma":[0.3957112,0.001267254,0.5713644,0.009311931,0.0005029817,0.002076204,0.001413298,0.0006742902,0.01767838],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05750225,"threshold_uncertainty_score":0.3041046,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04706505968501808,"score_gpt":0.3315448874974284,"score_spread":0.2844798278124104,"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."}}