{"id":"W2414074698","doi":"10.1002/sec.1453","title":"Two‐level security for message sequences","year":2016,"lang":"en","type":"article","venue":"Security and Communication Networks","topic":"Cryptographic Implementations and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Eavesdropping; Adversary; Computer security; Construct (python library); Encryption; Key (lock); Computer security model; Sequence (biology); Provable security; Information-theoretic security; Theoretical computer science; Computer network","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":[0.0008283502,0.000149356,0.0001689204,0.00007662724,0.0005737054,0.0001887703,0.0009761913,0.00008325622,0.0000252106],"category_scores_gemma":[0.00003583577,0.0001154772,0.00008143376,0.0002941574,0.0001974847,0.0006632365,0.0004174362,0.0001415534,0.000002224825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002312083,"about_ca_system_score_gemma":0.00003639417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001108359,"about_ca_topic_score_gemma":0.0006155638,"domain_scores_codex":[0.9987191,0.0002064545,0.0003016962,0.000322062,0.0001519838,0.000298704],"domain_scores_gemma":[0.9980552,0.0005811004,0.0001445026,0.0009623289,0.0001502411,0.0001066223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000100148,0.00005683922,0.0006098888,0.000009148009,0.00002204361,2.946352e-7,0.001920947,0.000009748936,0.00001585372,0.9542354,0.001306737,0.04180307],"study_design_scores_gemma":[0.002567608,0.0001543687,0.002473791,0.0001349738,0.00003030943,0.00002268035,0.0006834322,0.08500579,0.0002194653,0.8774078,0.03069158,0.0006082089],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04671406,0.005827466,0.934503,0.01005605,0.0002284215,0.0006885406,0.00008713664,0.0002527566,0.001642521],"genre_scores_gemma":[0.9827367,0.002932622,0.01366053,0.0004522449,0.00005212896,0.0001175804,0.00002547486,0.000007218494,0.00001545984],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9360227,"threshold_uncertainty_score":0.4709022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03194205530987518,"score_gpt":0.298445259408869,"score_spread":0.2665032040989938,"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."}}