{"id":"W2140811101","doi":"10.1002/sec.1082","title":"ReDD: recommendation‐based data dissemination in privacy‐preserving mobile social networks","year":2014,"lang":"en","type":"article","venue":"Security and Communication Networks","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Dissemination; Computer security; Network packet; Authentication (law); Internet privacy; Computer network; Protocol (science); Social network (sociolinguistics); Confidentiality; Quality (philosophy); Mobile phone; World Wide Web; Social media; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003821885,0.0007329206,0.001246962,0.001611008,0.001395807,0.001269002,0.002456503,0.001817855,0.001523624],"category_scores_gemma":[0.008205742,0.0004729439,0.0008438641,0.001765495,0.0008167303,0.002788833,0.002794864,0.001262179,0.0005979859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001161456,"about_ca_system_score_gemma":0.001344713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004147482,"about_ca_topic_score_gemma":0.003365109,"domain_scores_codex":[0.9960681,0.001427609,0.0003731198,0.0007253335,0.001123908,0.0002819917],"domain_scores_gemma":[0.9938676,0.002273742,0.0007486923,0.00172943,0.001079723,0.0003008516],"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":[0.001716521,0.0006999936,0.008632847,0.0009537413,0.0006257498,0.001473688,0.001226375,0.3157009,0.04877175,0.05327829,0.02023929,0.5466808],"study_design_scores_gemma":[0.0001375127,0.00032108,0.0008473186,0.00002870584,0.00006587068,0.0004061945,0.0001605269,0.9632806,0.01019174,0.01302616,0.0114603,0.00007397245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03713148,0.001289282,0.9537785,0.0009560222,0.0001846951,0.0006085862,0.0004338212,0.002599517,0.003018111],"genre_scores_gemma":[0.7876751,0.0007375167,0.2047496,0.0004455209,0.0001448703,0.0005125789,0.0005422232,0.0000570872,0.005135534],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004147482,"threshold_uncertainty_score":0.02021229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02557547304041716,"score_gpt":0.2935082090601328,"score_spread":0.2679327360197156,"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."}}