{"id":"W2003036326","doi":"10.1007/s10278-006-1051-4","title":"Pseudonymization of Radiology Data for Research Purposes","year":2006,"lang":"en","type":"article","venue":"Journal of Digital Imaging","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":69,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"DICOM; Computer science; Confidentiality; Identification (biology); Data set; Data science; Information retrieval; Data mining; Medical physics; Medicine; Artificial intelligence; Computer security","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.005697449,0.00055522,0.0006513573,0.00228902,0.001558544,0.002868136,0.0008842427,0.001385694,0.009607383],"category_scores_gemma":[0.02594062,0.000332231,0.0004094566,0.002409551,0.001540882,0.005154591,0.002746979,0.001615236,0.006434849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006691754,"about_ca_system_score_gemma":0.0016617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002054448,"about_ca_topic_score_gemma":0.000210447,"domain_scores_codex":[0.9921858,0.003890095,0.000897367,0.0008608132,0.001768564,0.0003973264],"domain_scores_gemma":[0.9671515,0.009371798,0.003317792,0.01504475,0.004213647,0.0009005197],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00493703,0.0003731469,0.006305381,0.001311363,0.00007445315,0.003071245,0.003843431,0.002261627,0.1690712,0.344899,0.03083278,0.4330193],"study_design_scores_gemma":[0.0003406608,0.001161864,0.008334546,0.0006878375,0.0001283672,0.01328714,0.001513668,0.04050476,0.2252363,0.1913696,0.5171885,0.000246855],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1305585,0.004036393,0.7997705,0.008572022,0.006117957,0.0009363001,0.004843456,0.003744984,0.0414198],"genre_scores_gemma":[0.5887547,0.002932373,0.3621877,0.00191037,0.003159385,0.001534975,0.005604231,0.0007423978,0.03317383],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9943026,"threshold_uncertainty_score":0.0321399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1037624118995043,"score_gpt":0.3747445670281317,"score_spread":0.2709821551286274,"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."}}