{"id":"W4415034636","doi":"10.1109/scam67354.2025.00008","title":"Detecting Exception-Related Behavioural Breaking Changes with UnCheckGuard","year":2025,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Java; Software; Class (philosophy); Value (mathematics); Transitive relation","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003883855,0.002070921,0.001199664,0.003932982,0.0008420355,0.002373403,0.003619697,0.00143697,0.003304031],"category_scores_gemma":[0.01925231,0.001507936,0.002076042,0.002337242,0.00246668,0.006315421,0.003776816,0.002381768,0.00232966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009892253,"about_ca_system_score_gemma":0.002213825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004495323,"about_ca_topic_score_gemma":0.005211189,"domain_scores_codex":[0.9902733,0.001083201,0.001024085,0.002589799,0.004130071,0.0008995337],"domain_scores_gemma":[0.979664,0.007982953,0.003328928,0.006337291,0.002241931,0.0004448624],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003566562,0.0007628652,0.2207298,0.002468029,0.0008051541,0.002524508,0.004352223,0.02347825,0.1582603,0.01322188,0.05132501,0.5185056],"study_design_scores_gemma":[0.0003766763,0.00144191,0.0695584,0.000535704,0.0006838788,0.003262205,0.001393783,0.2802346,0.5004699,0.02776522,0.1133037,0.0009740464],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.2326857,0.001998848,0.3184702,0.0005084304,0.0004762775,0.0004477395,0.005030198,0.4338828,0.006499712],"genre_scores_gemma":[0.7065313,0.0005908158,0.2464932,0.0008714284,0.0001115878,0.0004312905,0.01063624,0.02763361,0.006700485],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004495323,"threshold_uncertainty_score":0.02054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01406709763274214,"score_gpt":0.2341322335113351,"score_spread":0.2200651358785929,"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."}}