{"id":"W2900798344","doi":"10.1109/jbhi.2018.2881086","title":"Secure Similar Patients Query on Encrypted Genomic Data","year":2018,"lang":"en","type":"article","venue":"IEEE Journal of Biomedical and Health Informatics","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick; University of Manitoba","funders":"","keywords":"Computer science; Outsourcing; Encryption; Scalability; Cloud computing; Information privacy; Adversary; Information sensitivity; Flexibility (engineering); Search engine indexing; Computer security; Database; Information retrieval","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001414162,0.0001155759,0.0002586396,0.0002524661,0.0001989818,0.00008979756,0.001096666,0.00008843515,0.00001182948],"category_scores_gemma":[0.0000609471,0.00008113327,0.0000380876,0.0003013756,0.0001966301,0.0008834535,0.0002781882,0.0003370319,0.0000169826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003277489,"about_ca_system_score_gemma":0.0003092072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008987961,"about_ca_topic_score_gemma":0.000004430423,"domain_scores_codex":[0.997964,0.00004401441,0.001044993,0.00009860629,0.0005663693,0.0002820209],"domain_scores_gemma":[0.9980854,0.00006997555,0.0006986156,0.0004839684,0.0001585075,0.0005035032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001443971,0.0009712233,0.002941449,0.0006888175,0.0001236339,0.00001942072,0.01494788,0.000001900707,0.00002216106,0.01362302,0.4709022,0.4956138],"study_design_scores_gemma":[0.004458552,0.009175302,0.03772083,0.000713241,0.00002937756,0.0002272875,0.0004552442,0.05366557,0.00005965631,0.01090469,0.8820593,0.0005309023],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3521741,0.0004453031,0.630957,0.0112254,0.004086625,0.0003046155,0.0004044219,0.00005815939,0.0003443182],"genre_scores_gemma":[0.7055618,0.00305372,0.2545513,0.03440714,0.002254558,0.000001255877,0.0001521408,0.00001548542,0.000002605979],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4950829,"threshold_uncertainty_score":0.3308519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05171110410745283,"score_gpt":0.3204966208230047,"score_spread":0.2687855167155519,"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."}}