{"id":"W2472065388","doi":"10.2196/medinform.5571","title":"Data Safe Havens and Trust: Toward a Common Understanding of Trusted Research Platforms for Governing Secure and Ethical Health Research","year":2016,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Economic and Social Research Council; Engineering and Physical Sciences Research Council; Medical Research Council; National Institute for Social Care and Health Research; European Federation of Pharmaceutical Industries and Associations; Wellcome Trust; British Heart Foundation; Cancer Research UK","keywords":"Software deployment; Corporate governance; Public relations; Common Rule; Public trust; Research ethics; Big data; Computer security; Engineering ethics; Internet privacy; Business; Political science; Knowledge management; Medicine; Computer science; Engineering; Informed consent","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2275334,0.001375672,0.002831464,0.00682369,0.01944041,0.05826512,0.008471791,0.03012197,0.004178044],"category_scores_gemma":[0.2137857,0.00294174,0.003048248,0.005156689,0.1328423,0.07290053,0.04280851,0.03748025,0.001723673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02162329,"about_ca_system_score_gemma":0.05370947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007680445,"about_ca_topic_score_gemma":0.005094818,"domain_scores_codex":[0.727274,0.199189,0.02123643,0.01621936,0.02614843,0.009932828],"domain_scores_gemma":[0.6611762,0.192117,0.02714456,0.06925296,0.03202453,0.01828484],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001378257,0.00001145709,0.0002670205,0.00007712886,0.0000104612,0.0001201528,0.00903527,0.0003063584,0.00006089061,0.9846888,0.001934844,0.003473785],"study_design_scores_gemma":[0.00003344129,0.0000416502,0.0002015699,0.0008741016,0.00001909987,0.0003672186,0.006951207,0.001477926,0.0002630958,0.9289418,0.06074338,0.00008557778],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01758114,0.005372532,0.5502675,0.3306401,0.001744847,0.0009215227,0.0001433579,0.0004130626,0.09291597],"genre_scores_gemma":[0.6934502,0.004508026,0.2442712,0.04018192,0.001708584,0.002219355,0.0002188029,0.0005164829,0.01292537],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9915282,"threshold_uncertainty_score":0.9525889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8569933021897822,"score_gpt":0.6704935131906509,"score_spread":0.1864997889991313,"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."}}