{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003406003,0.00006318381,0.0001381024,0.0001936928,0.000135042,0.00009538743,0.0002353949,0.000008367069,0.0000162565],"category_scores_gemma":[0.0005875404,0.00004699912,0.000009303422,0.0003707799,0.0000726643,0.001965114,0.0001426954,0.0001257319,5.767873e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003116297,"about_ca_system_score_gemma":0.002295278,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1278476,"about_ca_topic_score_gemma":0.33581,"domain_scores_codex":[0.9986718,0.00002370146,0.0003022228,0.0001470019,0.0006939535,0.0001612635],"domain_scores_gemma":[0.9986207,0.0000838689,0.0002108165,0.0001076219,0.0007835073,0.0001934593],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001282924,0.00009162211,0.9559847,0.0005009174,0.0001558351,0.00005562026,0.005158807,0.0004935202,0.0003972405,0.004396774,0.008485585,0.02299649],"study_design_scores_gemma":[0.002029866,0.0008584732,0.8705694,0.001684811,0.00001063886,0.0006388904,0.003458924,0.1174541,0.00004427834,0.00001191744,0.003116947,0.0001217794],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8780885,0.00003952925,0.09903244,0.02071952,0.00007546345,0.0005671222,0.001359653,0.000008463108,0.0001092704],"genre_scores_gemma":[0.9778125,0.00002759494,0.02067553,0.0006556761,0.00004846769,0.000004364819,0.0007409208,0.00000379807,0.00003112901],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2079625,"threshold_uncertainty_score":0.8779601,"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."}}