{"id":"W4376955857","doi":"10.17762/ijritcc.v11i4s.6315","title":"Secure Digital Information Forward Using Highly Developed AES Techniques in Cloud Computing","year":2023,"lang":"en","type":"article","venue":"International Journal on Recent and Innovation Trends in Computing and Communication","topic":"Chaos-based Image/Signal Encryption","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Encryption; Communication source; Key (lock); Cryptography; Public-key cryptography; The Internet; Computer network; Computer security; Secure communication; World Wide Web","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":[0.001242539,0.00014983,0.0001540957,0.002760167,0.0001957828,0.0008070964,0.0005341732,0.00007971182,0.000005636389],"category_scores_gemma":[0.000161443,0.0001527901,0.00002330959,0.002627814,0.00004160461,0.001793873,0.0003707739,0.0004502034,0.000005708456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002487863,"about_ca_system_score_gemma":0.00005680814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001677954,"about_ca_topic_score_gemma":0.00000409657,"domain_scores_codex":[0.9983221,0.0001156895,0.0007967041,0.0001797577,0.0003990745,0.0001867339],"domain_scores_gemma":[0.9986289,0.0001826137,0.0004770703,0.0001783512,0.0004988842,0.000034157],"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":[0.00002914366,0.00004220809,0.002901043,0.00000530806,0.00001210817,0.000004190579,0.0009817354,0.002392827,0.0001351177,0.01881814,0.0002032807,0.9744749],"study_design_scores_gemma":[0.001796637,0.0001422706,0.03702578,0.0007682331,0.000004094159,0.0001680071,0.0003583534,0.922092,0.0009735735,0.01028274,0.02592775,0.0004606154],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.844295,0.00006422459,0.1459921,0.006913255,0.00053094,0.0001222007,0.000004536527,0.0002180947,0.001859669],"genre_scores_gemma":[0.9816838,0.0003451637,0.01728958,0.0004206868,0.00009527599,0.000001960294,0.0001359611,0.000007813815,0.00001976444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9740143,"threshold_uncertainty_score":0.7782849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04121510443575173,"score_gpt":0.3382664818838443,"score_spread":0.2970513774480926,"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."}}