{"id":"W3111257782","doi":"10.23889/ijpds.v5i5.1542","title":"Evaluating PPRL Vs Clear Text Linkage with Real-World Data","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Linkage (software); Identifier; Genetic linkage; Computer science; Record linkage; Population; Hash function; Genetics; Biology; Gene; Medicine","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":[0.0784123,0.001579769,0.001141998,0.009408238,0.001739067,0.004974357,0.003103511,0.003030711,0.004129244],"category_scores_gemma":[0.1939238,0.000469245,0.001838169,0.009418589,0.001703612,0.005644145,0.004785824,0.001330842,0.001502698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001875673,"about_ca_system_score_gemma":0.001624203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005476407,"about_ca_topic_score_gemma":0.005428284,"domain_scores_codex":[0.9442769,0.03114488,0.005777237,0.007391169,0.01049445,0.0009154077],"domain_scores_gemma":[0.7994889,0.1559485,0.0136459,0.01539351,0.01416411,0.001359123],"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":[0.00490954,0.001566823,0.2183055,0.00384269,0.003931398,0.0006285283,0.002069146,0.2907396,0.00415364,0.01514647,0.0377404,0.4169662],"study_design_scores_gemma":[0.0007254666,0.002457134,0.06275851,0.0007408006,0.000653614,0.0008091267,0.002419353,0.8637145,0.01714763,0.02265357,0.02563071,0.0002895097],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7044018,0.006293139,0.2429071,0.00274741,0.0007365755,0.001323167,0.01976809,0.01123905,0.01058363],"genre_scores_gemma":[0.6627031,0.0009341467,0.2952805,0.0004895769,0.0002758312,0.0008878401,0.03660668,0.0008145173,0.002007832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0784123,"threshold_uncertainty_score":0.4146888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6781494335367946,"score_gpt":0.5956232882520471,"score_spread":0.08252614528474744,"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."}}