{"id":"W2913840322","doi":"10.3390/info10020043","title":"Efficient Security Scheme for Disaster Surveillance UAV Communication Networks","year":2019,"lang":"en","type":"article","venue":"Information","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Redundancy (engineering); Computer science; Scheme (mathematics); Computer security; Overhead (engineering); Computer network; Reliability (semiconductor); Network packet; Confidentiality; Exploit","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000134359,0.00006241858,0.00006259883,0.00003745536,0.00004753351,0.00005025032,0.00008680605,0.00005512167,0.00002698651],"category_scores_gemma":[0.000006938297,0.00006433402,0.00002357212,0.0001144222,0.0000074362,0.000259341,0.0000145848,0.00005408709,0.0001187008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004387198,"about_ca_system_score_gemma":0.000003991922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003318021,"about_ca_topic_score_gemma":0.000004192769,"domain_scores_codex":[0.9996035,0.000005786186,0.0001909275,0.00003885631,0.00006191749,0.00009897378],"domain_scores_gemma":[0.9995795,0.00003377024,0.00004611216,0.0002431684,0.00007794335,0.00001947729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004216962,0.00000479771,0.0004253466,0.00003594234,0.000004385199,1.256101e-9,0.000480039,0.9938157,0.00001485081,0.002291508,0.00108953,0.001833646],"study_design_scores_gemma":[0.0002310389,0.000006204098,0.001209196,0.000008074887,0.000001452017,3.135569e-7,0.00007705716,0.9792994,0.00003286907,0.00005123783,0.01900331,0.00007989733],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2797943,0.00007513945,0.7083763,0.00008347915,0.0001836761,0.000747868,0.00002229215,0.0002406481,0.01047626],"genre_scores_gemma":[0.9945162,0.00002458381,0.004825989,0.00004680193,0.00002047039,0.00009051739,0.0004499559,0.000007499907,0.00001797042],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7147219,"threshold_uncertainty_score":0.2623465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002530971796951699,"score_gpt":0.1803711924201963,"score_spread":0.1778402206232446,"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."}}