{"id":"W3134664150","doi":"10.3390/computers10030025","title":"A Sensitive Data Access Model in Support of Learning Health Systems","year":2021,"lang":"en","type":"article","venue":"Computers","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Canadian Institutes of Health Research; Université de Sherbrooke","keywords":"Computer science; Suite; Protocol (science); Data access; Data science; Data exchange; Vulnerability (computing); Health care; Computer security; Distributed computing; Database; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004048351,0.00007240323,0.0002114041,0.0001062794,0.00005822393,0.00005495966,0.001301089,0.00005489217,4.534876e-7],"category_scores_gemma":[0.00001807606,0.00007988179,0.0000182644,0.0005295083,0.00004225766,0.0002199247,0.001687922,0.0002006743,0.000002459406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003403418,"about_ca_system_score_gemma":0.0002676955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007932398,"about_ca_topic_score_gemma":0.00002775712,"domain_scores_codex":[0.9989475,0.00008898869,0.0002495696,0.0004196052,0.0001121217,0.0001821999],"domain_scores_gemma":[0.9986919,0.00006681779,0.0001226072,0.0009979348,0.00007714547,0.00004356414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006031545,0.0004783233,0.003374641,0.000296666,0.00007350255,0.0001758645,0.00469115,0.32902,0.0003124403,0.5480366,0.02179208,0.0917427],"study_design_scores_gemma":[0.0001381723,0.00001691528,0.0003147314,0.00002395121,9.630298e-7,0.00003009714,0.00005244122,0.9969445,0.0002154192,0.0007503862,0.001442422,0.00006993832],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01088782,0.0001403323,0.9851018,0.003382941,0.0001159822,0.0001093859,0.000009290065,0.0001049466,0.0001475215],"genre_scores_gemma":[0.9556009,0.00004413245,0.04382237,0.0004519743,0.00001101715,0.000005918069,0.00003561608,0.000004363662,0.00002376442],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.944713,"threshold_uncertainty_score":0.3257484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05940188145440757,"score_gpt":0.325242689561109,"score_spread":0.2658408081067014,"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."}}