{"id":"W122504873","doi":"10.1007/978-3-642-36594-2_30","title":"Computational Soundness of Coinductive Symbolic Security under Active Attacks","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Soundness; Computer science; Encryption; Theoretical computer science; TRACE (psycholinguistics); Symmetric-key algorithm; Ciphertext; Mathematics; Computer security; Public-key cryptography; Programming language","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005529072,0.0006154942,0.0007725176,0.001018418,0.0002756854,0.0003718789,0.003405774,0.0004290071,0.00008937017],"category_scores_gemma":[0.00005553299,0.0005839249,0.0002398013,0.001014048,0.001805658,0.001384146,0.001747432,0.001061692,0.00005398342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002441614,"about_ca_system_score_gemma":0.0007850579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001202926,"about_ca_topic_score_gemma":0.00008912513,"domain_scores_codex":[0.9956152,0.00007188486,0.0006554347,0.001664783,0.001344244,0.0006484895],"domain_scores_gemma":[0.996292,0.0008103932,0.0005471961,0.001390755,0.0007374848,0.0002221802],"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":[0.00001907448,0.0001827614,0.00009073618,0.00009657415,0.00008102031,0.00003126379,0.004828407,0.03885871,0.00005423988,0.8216643,0.00009933762,0.1339936],"study_design_scores_gemma":[0.0003128778,0.0001345222,0.0009438411,0.0002044901,0.00001226489,0.00005697466,0.000001638897,0.1265085,0.0005982326,0.8703923,0.0002243206,0.0006100844],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00228701,0.0001999607,0.9917486,0.0003525475,0.001344763,0.0005329383,0.00008754501,0.0001136607,0.003332979],"genre_scores_gemma":[0.7788489,0.00003114472,0.2197945,0.0008597207,0.0003350394,0.00001691111,0.00005360425,0.00003590236,0.00002422516],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7765619,"threshold_uncertainty_score":0.9996612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01716209837868851,"score_gpt":0.2580138085464211,"score_spread":0.2408517101677326,"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."}}