{"id":"W3115634801","doi":"10.23889/ijpds.v5i5.1541","title":"How Are Linkage Results Using Privacy-Preserving Record Linkage Different?","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Linkage (software); Record linkage; Computer science; Internet privacy; Genetics; Biology; Medicine; Environmental health; Gene","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":[0.1307216,0.001782771,0.002804208,0.009375369,0.003451942,0.01973231,0.004374139,0.003148151,0.006968302],"category_scores_gemma":[0.3138482,0.0008496766,0.004099349,0.01444945,0.003999814,0.01479098,0.006712642,0.002484215,0.003450897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002718836,"about_ca_system_score_gemma":0.004548976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004128536,"about_ca_topic_score_gemma":0.003058803,"domain_scores_codex":[0.8788203,0.06550822,0.01088658,0.01450011,0.02665761,0.003627098],"domain_scores_gemma":[0.7761664,0.1252309,0.01473272,0.05189413,0.03065292,0.001322994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00220619,0.0005740761,0.1820909,0.002939936,0.004220381,0.0007989619,0.006221179,0.04836208,0.003397014,0.1061212,0.04301444,0.6000535],"study_design_scores_gemma":[0.000613754,0.001062603,0.05275214,0.002573338,0.002255224,0.003815031,0.01350433,0.146394,0.0347943,0.6268817,0.1145482,0.0008053846],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2106034,0.01100705,0.6985111,0.02195814,0.002355397,0.001283671,0.0162818,0.009499041,0.02850054],"genre_scores_gemma":[0.5554044,0.002679049,0.4225579,0.002071717,0.0005450684,0.0004965271,0.0111971,0.001861582,0.003186639],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1307216,"threshold_uncertainty_score":0.6913301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5276143466944776,"score_gpt":0.4968237018665874,"score_spread":0.03079064482789023,"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."}}