{"id":"W3112495257","doi":"10.23889/ijpds.v5i5.1630","title":"Using A Privacy Preserving Record Linkage to Facilitate an Ongoing Crosswalk Between Research and Health Administrative Databases","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":"Indoc Research; Ontario Brain Institute","funders":"","keywords":"Schema crosswalk; Record linkage; Computer science; Database; Data science; Medicine; Engineering; Transport engineering","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":[0.1865442,0.001168233,0.001036747,0.009764626,0.004486123,0.01082865,0.0050797,0.001900074,0.01253737],"category_scores_gemma":[0.2257032,0.001645011,0.00281247,0.01077566,0.002201548,0.009015946,0.01717373,0.002962884,0.006731251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004804084,"about_ca_system_score_gemma":0.02772547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006506328,"about_ca_topic_score_gemma":0.008494636,"domain_scores_codex":[0.8009002,0.1223456,0.02368625,0.01741662,0.03195954,0.003691864],"domain_scores_gemma":[0.7132887,0.08294238,0.04167438,0.09701823,0.05997806,0.005098188],"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":[0.0009518315,0.001261535,0.04100986,0.003026761,0.0005858396,0.000827993,0.02081759,0.00849746,0.01029528,0.08958496,0.04936071,0.7737802],"study_design_scores_gemma":[0.0008972606,0.00283899,0.0493313,0.004273065,0.0007901958,0.002213866,0.01653359,0.06499162,0.07224362,0.1084488,0.6763136,0.001124056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02422274,0.0002752743,0.9291355,0.004709824,0.0003579163,0.01539554,0.006455425,0.006403326,0.01304451],"genre_scores_gemma":[0.03810466,0.0001241205,0.9463219,0.0004185454,0.00007507871,0.007302548,0.003932974,0.0004321126,0.003288009],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1865442,"threshold_uncertainty_score":0.9865519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9620375251486527,"score_gpt":0.6997589936175305,"score_spread":0.2622785315311222,"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."}}