{"id":"W1555588376","doi":"10.1002/spe.2108","title":"Linguistic security testing for text communication protocols","year":2012,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Web Application Security Vulnerabilities","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Sheridan College","funders":"","keywords":"Computer science; Syntax; Protocol (science); Programming language; Grammar; Test (biology); Formal grammar; Cryptographic protocol; Communications protocol; Natural language processing; Rule-based machine translation; Computer security; Computer network; Linguistics","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0009031112,0.0001209457,0.0001222423,0.00003538316,0.0004484293,0.0002681702,0.0005909656,0.00005613445,0.000004650947],"category_scores_gemma":[0.01348972,0.0001210467,0.00002261584,0.0002514066,0.0001282772,0.002247702,0.0003051556,0.0001580482,0.00001697888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003413697,"about_ca_system_score_gemma":0.00006230359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006360347,"about_ca_topic_score_gemma":0.000001980449,"domain_scores_codex":[0.9988496,0.0001220867,0.000239233,0.0002849966,0.0001960326,0.0003080777],"domain_scores_gemma":[0.9950743,0.003421212,0.0002014719,0.0007630237,0.0004086009,0.0001313628],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006604844,0.0007596861,0.02492058,0.0003653989,0.00002130187,0.00000128804,0.4586945,0.000005299109,0.0007274644,0.4195487,0.0009281113,0.09396159],"study_design_scores_gemma":[0.0008049064,0.0003134101,0.003382823,0.0001812788,0.00002475539,0.0001751723,0.009558026,0.005408937,0.005308905,0.05051617,0.9234447,0.0008808485],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02941092,0.001485124,0.9507836,0.002390164,0.0002103872,0.010916,0.000008526086,0.0008715359,0.003923696],"genre_scores_gemma":[0.618839,0.000006815902,0.3701835,0.0005488215,0.00008527575,0.01030823,0.000001896067,0.000007353142,0.00001910061],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9225166,"threshold_uncertainty_score":0.9948201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05456387560853018,"score_gpt":0.3688064179561888,"score_spread":0.3142425423476586,"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."}}