{"id":"W4402405562","doi":"10.23889/ijpds.v9i5.2882","title":"Balancing Privacy and Precision: Evaluating Meta-Analysis for National Health Data Integration in Canada","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Meta-analysis; Data science; Data integration; Data mining; Internet privacy; Computer security; 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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2370244,0.003876413,0.01421148,0.009256925,0.002054723,0.007379466,0.005065576,0.003642396,0.002511495],"category_scores_gemma":[0.443727,0.001963235,0.05096554,0.009905323,0.002516604,0.002869541,0.003672631,0.004262789,0.0001760173],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01559617,"about_ca_system_score_gemma":0.02278311,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1550914,"about_ca_topic_score_gemma":0.1520853,"domain_scores_codex":[0.7202001,0.2264764,0.02367884,0.01162864,0.01633086,0.001685152],"domain_scores_gemma":[0.5651016,0.3759223,0.01997432,0.01938391,0.01788687,0.001731087],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003517796,0.00003519466,0.01482577,0.02451101,0.927148,0.0001380335,0.0001877715,0.007627638,0.0001572216,0.001152241,0.001211812,0.01948752],"study_design_scores_gemma":[0.002243395,0.0004798197,0.01117754,0.008387084,0.9569975,0.0001401677,0.0001225674,0.009753207,0.0004401629,0.005660118,0.004478929,0.0001195334],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"review","genre_gemma":"methods","genre_scores_codex":[0.04571031,0.8219417,0.1035006,0.008792195,0.002270179,0.006539748,0.006444698,0.0008294044,0.003971115],"genre_scores_gemma":[0.8172566,0.069722,0.09516659,0.003654833,0.0006382305,0.009104599,0.003118724,0.0004004834,0.0009380437],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9844038,"threshold_uncertainty_score":0.9408848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8670855062200638,"score_gpt":0.7085032493344741,"score_spread":0.1585822568855897,"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."}}