{"id":"W2339624507","doi":"10.1109/allerton.2015.7447126","title":"Erasure adversarial wiretap channels","year":2015,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Security Techniques","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Code word; Secrecy; Computer science; Erasure; Upper and lower bounds; Adversary; Code (set theory); Channel (broadcasting); Decoding methods; Erasure code; Binary erasure channel; Constant (computer programming); Fraction (chemistry); Theoretical computer science; Algorithm; Computer network; Mathematics; Channel capacity; Computer security","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":[0.001403126,0.0009122951,0.0009916235,0.0005962506,0.0008229712,0.001565157,0.001268383,0.001573424,0.003815877],"category_scores_gemma":[0.008262478,0.0004679309,0.0007233397,0.0009732113,0.002213313,0.003074452,0.002868611,0.002590185,0.0008463971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000813928,"about_ca_system_score_gemma":0.0008651979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008253842,"about_ca_topic_score_gemma":0.0006579897,"domain_scores_codex":[0.9979916,0.0006353503,0.00008799686,0.0003074188,0.0005337491,0.0004439958],"domain_scores_gemma":[0.9924114,0.004608801,0.0006274152,0.00155697,0.0005951313,0.0002004456],"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":[0.0004873197,0.00005991119,0.0005161903,0.0001680264,0.00005816696,0.0006914514,0.0002569768,0.282067,0.01196782,0.6765684,0.004538344,0.02262036],"study_design_scores_gemma":[0.00003546325,0.00009705369,0.0001191531,0.00003950455,0.0000276728,0.0003435023,0.00005381684,0.8408203,0.008912724,0.1449339,0.004573952,0.00004300255],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03466329,0.0002477257,0.9517238,0.000558101,0.0000982032,0.00007961236,0.0003934751,0.0004295619,0.0118062],"genre_scores_gemma":[0.9240452,0.0007113189,0.06188479,0.000287597,0.0001300726,0.0003160514,0.0003138499,0.00008965534,0.01222143],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003815877,"threshold_uncertainty_score":0.01276541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03639348240407562,"score_gpt":0.238814332068982,"score_spread":0.2024208496649064,"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."}}