{"id":"W3006968785","doi":"10.23889/ijpds.v5i1.1144","title":"Developing a comprehensive database with sensitive health information: A profile of people living with HIV in Newfoundland and Labrador, Canada","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"HIV/AIDS Research and Interventions","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bruyère; University of Ottawa; St. John’s Health Sciences Centre; Newfoundland and Labrador Centre for Applied Health Research; Memorial University of Newfoundland","funders":"Canadian Institutes of Health Research","keywords":"Confidentiality; Cohort; Database; Computer science; Context (archaeology); Data governance; Population; Medical record; Health care; Medicine; Data quality; Business; Environmental health; Geography; Computer security; Political science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002974768,0.0001763857,0.0002525359,0.002058747,0.009411776,0.00375689,0.001531748,0.0005010887,0.002249315],"category_scores_gemma":[0.008827265,0.0003396272,0.0003003683,0.005440867,0.001951648,0.001826552,0.00276274,0.001030537,0.0002587588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05043739,"about_ca_system_score_gemma":0.09845604,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9838679,"about_ca_topic_score_gemma":0.9908664,"domain_scores_codex":[0.9966862,0.0006070493,0.0003796146,0.0003236202,0.001005261,0.0009982921],"domain_scores_gemma":[0.9880152,0.001827362,0.001444188,0.0005683384,0.00461411,0.003530834],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007589185,0.0001766906,0.8449975,0.0003393537,0.00004305817,0.003201195,0.08084612,0.0004696964,0.0008835305,0.002395822,0.02465062,0.04192054],"study_design_scores_gemma":[0.00001702425,0.0001138823,0.6687396,0.0007079378,0.00004856199,0.002034248,0.248131,0.001320837,0.0005029427,0.0005508852,0.07771746,0.0001156001],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9594668,0.001300609,0.001114844,0.01473744,0.00003659061,0.0008908001,0.009025909,0.00008070662,0.01334647],"genre_scores_gemma":[0.9792251,0.002179591,0.006344645,0.003488061,0.00002101823,0.0003280595,0.004191785,0.00003595369,0.004185839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05043739,"threshold_uncertainty_score":0.3659506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0537347801362217,"score_gpt":0.3664706486001829,"score_spread":0.3127358684639612,"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."}}