{"id":"W2085478526","doi":"10.1109/msp.2009.47","title":"Privacy Interests in Prescription Data, Part 2: Patient Privacy","year":2009,"lang":"en","type":"article","venue":"IEEE Security & Privacy","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Genome Canada; Dalhousie University; University of Ottawa","funders":"","keywords":"Medical prescription; Scrutiny; Internet privacy; Information privacy; Pharmacy; Business; Privacy policy; Privacy by Design; Masking (illustration); Patient privacy; Privacy software; Privacy laws of the United States; Family medicine; Medicine; Health care; Computer science; Political science; Nursing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.009544273,0.0003352648,0.0005072252,0.001095337,0.003818479,0.007332887,0.000964975,0.007666857,0.005840595],"category_scores_gemma":[0.02181719,0.0004605984,0.0009033186,0.002390788,0.007988237,0.007412032,0.002558152,0.005331012,0.0009113338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004608426,"about_ca_system_score_gemma":0.006727541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01207893,"about_ca_topic_score_gemma":0.01172902,"domain_scores_codex":[0.9867697,0.005367887,0.0007659615,0.0007762061,0.005256102,0.001064078],"domain_scores_gemma":[0.9835542,0.01090072,0.00120051,0.001955245,0.001893674,0.000495579],"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":[0.0000705796,0.00005379069,0.006787255,0.0002986154,0.0000343744,0.001090297,0.009610482,0.0008732078,0.001307305,0.8020404,0.1000322,0.07780131],"study_design_scores_gemma":[0.0000216126,0.00008581808,0.006953496,0.0007114104,0.00005687774,0.003471807,0.003841015,0.001340886,0.002472831,0.197495,0.7834824,0.00006688575],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02620512,0.03731522,0.06370109,0.5100057,0.002934296,0.0002997992,0.001248372,0.0001684191,0.3581221],"genre_scores_gemma":[0.6583217,0.04260895,0.0326067,0.1420577,0.007578421,0.0004261161,0.0007458382,0.0001510008,0.1155035],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01207893,"threshold_uncertainty_score":0.05047554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04833679831184508,"score_gpt":0.2999858548829728,"score_spread":0.2516490565711277,"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."}}