{"id":"W7117111774","doi":"10.3390/jcp6010002","title":"Using Secure Multi-Party Computation to Create Clinical Trial Cohorts","year":2025,"lang":"en","type":"article","venue":"Journal of Cybersecurity and Privacy","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Global Health Research","funders":"","keywords":"Interoperability; Cryptography; Health care; Key (lock); Secure multi-party computation; Clinical trial; Python (programming language); Data integrity; Data anonymization","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.012282,0.0003998429,0.0005815562,0.0008362051,0.0008701635,0.002162656,0.001284591,0.0007302159,0.005992213],"category_scores_gemma":[0.03702241,0.0004366773,0.0008917685,0.0009654224,0.001399423,0.002804484,0.00472805,0.001529086,0.00149293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009280656,"about_ca_system_score_gemma":0.004733329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005356447,"about_ca_topic_score_gemma":0.0006608202,"domain_scores_codex":[0.9905533,0.005034322,0.0005541378,0.00112208,0.002165196,0.0005709211],"domain_scores_gemma":[0.973421,0.01106664,0.002122509,0.01100606,0.001354263,0.001029521],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002788822,0.0004550272,0.01661468,0.0005089205,0.0003425415,0.001060215,0.001192398,0.2630991,0.02726265,0.3142439,0.007519105,0.3649127],"study_design_scores_gemma":[0.0003976672,0.000580826,0.001949603,0.00008473633,0.00007482121,0.0005109914,0.0001630547,0.6290036,0.03694068,0.3045032,0.02573059,0.00006011216],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03873108,0.0001545082,0.953777,0.0007894486,0.00009618451,0.0007263162,0.0004162042,0.001119584,0.004189692],"genre_scores_gemma":[0.6749241,0.0001815866,0.3203543,0.0003255455,0.00007896586,0.0008342239,0.000555595,0.0001548383,0.002590847],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.012282,"threshold_uncertainty_score":0.06495422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1026479021444132,"score_gpt":0.413843831321857,"score_spread":0.3111959291774438,"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."}}