{"id":"W3109797377","doi":"10.18280/isi.250507","title":"Number of Pixel Change Rate and Unified Average Changing Intensity for Sensitivity Analysis of Encrypted inSAR Interferogram","year":2020,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Encryption; Sensitivity (control systems); Computer science; Pixel; Cryptosystem; Advanced Encryption Standard; Key (lock); Algorithm; Mode (computer interface); Artificial intelligence; Electronic engineering; Computer security; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008071916,0.0005185768,0.0003016309,0.001896116,0.0002288503,0.0004967449,0.0002984623,0.0003876572,0.001756075],"category_scores_gemma":[0.004889105,0.0001344713,0.0003624637,0.001215676,0.0003736228,0.0008419356,0.0003516603,0.0003253639,0.0002748404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004628287,"about_ca_system_score_gemma":0.0001985432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009160012,"about_ca_topic_score_gemma":0.0006716259,"domain_scores_codex":[0.9989024,0.0001888998,0.00008254618,0.0001848523,0.000553188,0.00008799255],"domain_scores_gemma":[0.9974127,0.001226734,0.0004288311,0.0003217403,0.0005476099,0.00006227295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001367767,0.0004455216,0.0748911,0.0009288177,0.0002850422,0.001559236,0.001014238,0.2246094,0.3797823,0.006528473,0.002072268,0.3065159],"study_design_scores_gemma":[0.00001565644,0.0009810047,0.08399358,0.00005875492,0.0001152445,0.001872708,0.0005000617,0.6840769,0.222238,0.002228306,0.003782215,0.0001376322],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7884815,0.001003845,0.1998995,0.0001347293,0.0001289829,0.0001892082,0.0007617836,0.001206702,0.008193805],"genre_scores_gemma":[0.9797673,0.0001861484,0.01876974,0.00002328849,0.00001559679,0.00006449277,0.0003055741,0.00005280359,0.0008150668],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001896116,"threshold_uncertainty_score":0.005874634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01987626651851626,"score_gpt":0.2352791610311686,"score_spread":0.2154028945126524,"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."}}