{"id":"W4389050893","doi":"10.2196/47248","title":"Best Practices in Evolving Privacy Frameworks for Patient Age Data: Census Data Study","year":2023,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Health Insurance Portability and Accountability Act; Context (archaeology); Demography; Population; Geography; Medicine; Actuarial science; Computer science; Business; Confidentiality; Computer security; Sociology","routes":{"ca_aff":false,"ca_fund":false,"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":[0.187403,0.0007496786,0.0007726737,0.005388085,0.002585071,0.009677365,0.00433372,0.003220933,0.001543905],"category_scores_gemma":[0.5075994,0.001211599,0.001860086,0.008048165,0.003206946,0.013947,0.006451781,0.004088706,0.0005124696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007783327,"about_ca_system_score_gemma":0.01504228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03931208,"about_ca_topic_score_gemma":0.03026129,"domain_scores_codex":[0.740216,0.2175545,0.01175746,0.008177612,0.02015324,0.002141223],"domain_scores_gemma":[0.4387806,0.4122159,0.02947438,0.07446342,0.0406724,0.004393362],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006101666,0.0004973528,0.3438034,0.001303358,0.0006685584,0.0005828995,0.02150505,0.05171724,0.0008498465,0.2052153,0.0384975,0.3347493],"study_design_scores_gemma":[0.0003653242,0.0006475115,0.1099498,0.006659684,0.0004744004,0.001721006,0.02908831,0.2852176,0.005466042,0.3216658,0.2381028,0.0006417683],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3025036,0.00967331,0.4883302,0.1472405,0.000780163,0.002636043,0.01215028,0.001476793,0.0352091],"genre_scores_gemma":[0.6512263,0.00332049,0.3350424,0.004134403,0.0002857792,0.0009758266,0.004075769,0.0002224189,0.0007167332],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.187403,"threshold_uncertainty_score":0.9910937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3756075585671576,"score_gpt":0.5126804688932458,"score_spread":0.1370729103260883,"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."}}