{"id":"W4226205863","doi":"10.1109/qrs54544.2021.00076","title":"Vulnerability Analysis of Similar Code","year":2021,"lang":"en","type":"article","venue":"2021 IEEE 21st International Conference on Software Quality, Reliability and Security (QRS)","topic":"Software Engineering Research","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"New York Institute of Technology","funders":"","keywords":"Computer science; Secure coding; Vulnerability (computing); Software security assurance; Code (set theory); Computer security; Code review; Static program analysis; Domain (mathematical analysis); Software; Scripting language; Source code; Vulnerability assessment; Security bug; Application security; Software engineering; Information security; Programming language; Software development; Security service; Mathematics","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","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002714594,0.0003411519,0.0008067535,0.0003942791,0.0001511052,0.0003221785,0.001420049,0.0002509984,0.0008414883],"category_scores_gemma":[0.008373417,0.0003548944,0.000401315,0.001502283,0.0003321307,0.000479821,0.0006532902,0.0007137656,0.00002450716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002105158,"about_ca_system_score_gemma":0.0004377986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003019177,"about_ca_topic_score_gemma":0.0003212671,"domain_scores_codex":[0.9948832,0.0007989472,0.0009711669,0.001356567,0.001559695,0.0004303783],"domain_scores_gemma":[0.9923891,0.003222526,0.0002445735,0.001711118,0.002147551,0.0002851407],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002295269,0.003131598,0.4963746,0.0008107368,0.002580795,0.0001081401,0.006615764,0.008281243,0.001489718,0.4604037,0.0007498116,0.01922441],"study_design_scores_gemma":[0.002419007,0.0005447202,0.5289764,0.0003785935,0.0004501328,0.00003116604,0.00110757,0.2946349,0.01605869,0.147408,0.005687853,0.002302966],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8105078,0.0001270845,0.1819715,0.003843261,0.001149081,0.0002782122,0.0007780195,0.0002670893,0.001078024],"genre_scores_gemma":[0.9898568,0.0002393263,0.009191988,0.0002687005,0.00007735227,0.00003327027,0.0001208913,0.00001395305,0.0001976668],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3129956,"threshold_uncertainty_score":0.9999795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06034556526092438,"score_gpt":0.3613439035872422,"score_spread":0.3009983383263178,"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."}}