{"id":"W4237087222","doi":"10.2196/jmi.v6i1.8286","title":"Secure and Efficient Regression Analysis Using a Hybrid Cryptographic Framework: Development and Evaluation","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Chaos-based Image/Signal Encryption","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Cryptography; Computer science; Regression; Regression analysis; Computer security; Statistics; Mathematics; Machine learning","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":[0.003677853,0.0009981685,0.0008995269,0.001327172,0.0004896398,0.001644945,0.002146268,0.001070826,0.002722241],"category_scores_gemma":[0.007323205,0.0003479696,0.000843889,0.0008949516,0.001428204,0.00358675,0.002132308,0.001557564,0.001065198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001251024,"about_ca_system_score_gemma":0.002136798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001052573,"about_ca_topic_score_gemma":0.0005725343,"domain_scores_codex":[0.9939238,0.001387687,0.0003136275,0.0003812632,0.003355041,0.0006385399],"domain_scores_gemma":[0.9951063,0.001314002,0.0006837624,0.001351256,0.001344156,0.0002004694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00244578,0.001196888,0.005590561,0.001443705,0.0003774937,0.0008247533,0.000284267,0.2922552,0.08058888,0.1377061,0.01318973,0.4640966],"study_design_scores_gemma":[0.0001806531,0.00124895,0.0007970866,0.00008857895,0.00009422753,0.0007475428,0.00007865057,0.9335269,0.04714948,0.007529595,0.008488987,0.00006932262],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1261707,0.003411652,0.8529371,0.001035222,0.000202175,0.0008977638,0.0001973256,0.004469581,0.01067848],"genre_scores_gemma":[0.7538323,0.002205011,0.2394656,0.0003093029,0.00009481794,0.0002953715,0.0003825405,0.0002309971,0.003183856],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003677853,"threshold_uncertainty_score":0.0194506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05190114495221237,"score_gpt":0.3373478473198193,"score_spread":0.2854467023676069,"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."}}