{"id":"W2699584971","doi":"10.1109/tcomm.2017.2764892","title":"Secure Broadcasting Using Independent Secret Keys","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Wireless Communication Security Techniques","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Science Foundation","keywords":"Computer science; Broadcasting (networking); Computer network; Transmitter; Channel (broadcasting); Coding (social sciences); Channel capacity; Encryption; Computer security; Topology (electrical circuits); Mathematics","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":[0.001870497,0.001018577,0.001407084,0.0008767307,0.0009404831,0.002157486,0.001276041,0.00191648,0.003513483],"category_scores_gemma":[0.008956195,0.0006512449,0.0008171386,0.001826287,0.002240908,0.005772461,0.002443573,0.002239029,0.000890441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002007972,"about_ca_system_score_gemma":0.001449296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00111988,"about_ca_topic_score_gemma":0.0006638913,"domain_scores_codex":[0.9974617,0.000886241,0.0001075771,0.0003562596,0.0007245481,0.0004636645],"domain_scores_gemma":[0.9933376,0.004884524,0.0005552917,0.0006624024,0.0004344189,0.0001257904],"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":[0.0004684784,0.00006009387,0.000365335,0.0004667891,0.00007810796,0.0004297227,0.0004402572,0.2899112,0.01450375,0.6588752,0.003025427,0.03137564],"study_design_scores_gemma":[0.00005704549,0.0001070534,0.0001502664,0.00003862712,0.00004739763,0.0002891944,0.0001252616,0.7281634,0.006584201,0.2600549,0.004345858,0.0000367388],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0454591,0.0008443546,0.9381218,0.0008515119,0.00008163548,0.00007520161,0.0001842954,0.0002043126,0.01417778],"genre_scores_gemma":[0.8832252,0.002549621,0.1020298,0.0001706608,0.0002498961,0.0001961386,0.0002942178,0.0001167314,0.01116779],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003513483,"threshold_uncertainty_score":0.01456898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07183492949968856,"score_gpt":0.3164186923111612,"score_spread":0.2445837628114726,"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."}}