{"id":"W4405488082","doi":"10.1109/jiot.2024.3519458","title":"EdgeCrypt Tracker: Object Tracking With Differential Encryption for IoAAV Surveillance","year":2024,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Security in Wireless Sensor Networks","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Nuclear Safety Commission","keywords":"Computer science; Computer vision; Encryption; Tracking (education); Video tracking; Differential (mechanical device); Artificial intelligence; Object (grammar); Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004750335,0.0004542114,0.0004010333,0.0005868221,0.0002890754,0.0006292336,0.0007373467,0.0005315596,0.0009165145],"category_scores_gemma":[0.001020494,0.0001768572,0.00027506,0.0004163857,0.0002746418,0.001051354,0.0006717197,0.0005616318,0.0004805498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005574506,"about_ca_system_score_gemma":0.0005521733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001764081,"about_ca_topic_score_gemma":0.002526063,"domain_scores_codex":[0.9996754,0.00003702416,0.00001714603,0.00006722943,0.0001667903,0.00003635163],"domain_scores_gemma":[0.9997012,0.00006112198,0.00004492661,0.00007531508,0.00009779652,0.00001951868],"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":[0.0005457788,0.0001137059,0.006446175,0.0001228845,0.00009397841,0.000353017,0.0001641879,0.04228937,0.1379926,0.01360159,0.008556857,0.7897199],"study_design_scores_gemma":[0.00004198786,0.0002648991,0.002444976,0.00002762156,0.00004001507,0.0007624502,0.00003233425,0.854349,0.1243704,0.002940214,0.0146843,0.00004168857],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02898533,0.000650338,0.9654483,0.00009969423,0.0001238918,0.00007007973,0.00008977792,0.001844837,0.002687815],"genre_scores_gemma":[0.5459526,0.0006413771,0.4466,0.0002677246,0.00007173714,0.00008079142,0.0005413049,0.0001554583,0.005689069],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001764081,"threshold_uncertainty_score":0.004044592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01554218764214897,"score_gpt":0.2546454649711072,"score_spread":0.2391032773289582,"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."}}