{"id":"W2979425925","doi":"10.1049/iet-com.2019.0657","title":"T_CAFE: A Trust based Security approach for Opportunistic IoT","year":2019,"lang":"en","type":"article","venue":"IET Communications","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer network; Computer science; Identifier; Network packet; Internet of Things; Routing protocol; Computer security; Unique identifier; The Internet; Latency (audio); Telecommunications; 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":[0.0005323196,0.000169618,0.000247443,0.00008375292,0.0003347809,0.0001560876,0.003016005,0.0001149143,0.00004955115],"category_scores_gemma":[0.00001820606,0.0001705826,0.0001385684,0.0003294726,0.0001255825,0.0001467263,0.000522745,0.0002618042,0.00006223132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004509078,"about_ca_system_score_gemma":0.0003025764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001872855,"about_ca_topic_score_gemma":0.000004393509,"domain_scores_codex":[0.9986392,0.000129166,0.0003396768,0.0003612017,0.0002044661,0.000326265],"domain_scores_gemma":[0.9948536,0.0005519172,0.000154026,0.004082304,0.0001779509,0.0001801963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003274671,0.0009999083,0.001205522,0.0001171646,0.00007082045,0.00000305701,0.0007788361,0.0003462048,0.000074194,0.9197515,0.02541141,0.05120862],"study_design_scores_gemma":[0.0005013807,0.00006261052,0.00007268671,0.0000154486,0.00001866606,0.00000702803,0.00005268032,0.9347479,0.000004475599,0.005009979,0.05929931,0.0002078408],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002983526,0.0001381744,0.9349541,0.002312907,0.0001890324,0.0006786481,0.00006752839,0.0002153959,0.06114583],"genre_scores_gemma":[0.7794681,0.00002720743,0.218139,0.001024583,0.00003705108,0.0001687639,0.0002586158,0.00001532177,0.0008612931],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9344017,"threshold_uncertainty_score":0.6956158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04525479578256403,"score_gpt":0.2788353855208653,"score_spread":0.2335805897383013,"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."}}