{"id":"W150269170","doi":"","title":"Security tools: TSIEM and AppScan source for security","year":2011,"lang":"en","type":"article","venue":"Conference of the Centre for Advanced Studies on Collaborative Research","topic":"Information and Cyber Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer security; Security information and event management; Computer science; Information security audit; Software security assurance; Security service; Security testing; Audit; Information security management; Information security; Cloud computing security; Encryption; Computer security model; Security through obscurity; Information security standards; Application security; Security bug; Security engineering; Business; Cloud computing; Accounting; Network security policy; Operating system","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":[],"consensus_categories":[],"category_scores_codex":[0.001226411,0.0001949072,0.0003469503,0.0001074594,0.0007259825,0.000112752,0.000974978,0.00006812937,0.000006022988],"category_scores_gemma":[0.001948625,0.0001384929,0.00008527742,0.0007428278,0.000565032,0.0006222161,0.000635593,0.0002483657,0.000003069897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001047337,"about_ca_system_score_gemma":0.0003053537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005673843,"about_ca_topic_score_gemma":0.0001826549,"domain_scores_codex":[0.9980039,0.0002603214,0.000353716,0.0004043352,0.000473951,0.000503765],"domain_scores_gemma":[0.993823,0.0009285379,0.0002243378,0.0005616665,0.004352721,0.0001097412],"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":[0.0004138149,0.0001783087,0.00009965046,0.0003185879,0.0001271384,3.371423e-7,0.1189116,0.00001561129,0.0001343869,0.8542779,0.00475776,0.02076489],"study_design_scores_gemma":[0.005637652,0.002241147,0.0004417634,0.00067691,0.00003693796,0.000002198292,0.1637315,0.01957307,0.1990543,0.3799809,0.2276836,0.0009399662],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6794314,0.006529265,0.1662165,0.04191196,0.005422729,0.03494421,0.002977434,0.0006932336,0.0618733],"genre_scores_gemma":[0.9950441,0.000302833,0.003815039,0.0001059953,0.00002921195,0.0001945669,0.000003513852,0.0000093839,0.0004954226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.474297,"threshold_uncertainty_score":0.5647579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1450953302047891,"score_gpt":0.3758630512764004,"score_spread":0.2307677210716113,"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."}}