{"id":"W2106712039","doi":"10.1109/ase.2008.19","title":"Automatic Inference of Frame Axioms Using Static Analysis","year":2008,"lang":"en","type":"article","venue":"","topic":"Security and Verification in Computing","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Axiom; Computer science; Theoretical computer science; Pointer (user interface); Inference; Frame (networking); Static analysis; Separation logic; Set (abstract data type); Algorithm; Class (philosophy); Data mining; Programming language; Artificial intelligence; 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":[],"consensus_categories":[],"category_scores_codex":[0.000162596,0.00006782322,0.0001757966,0.0002307277,0.0001058194,0.00003273349,0.0005048687,0.00003066193,0.0001054771],"category_scores_gemma":[0.00007938382,0.00006300585,0.0000742531,0.001626624,0.00005818868,0.0002435187,0.0001068558,0.00005858961,0.00001414587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001948919,"about_ca_system_score_gemma":0.00008242885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001798109,"about_ca_topic_score_gemma":0.000003112668,"domain_scores_codex":[0.9991099,0.00005028097,0.000292953,0.0001876676,0.0002292142,0.000129983],"domain_scores_gemma":[0.9990314,0.000226605,0.0001441717,0.0004536093,0.00009957851,0.00004462877],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003909558,0.0006921799,0.07696209,0.0002676922,0.001210568,0.00003404456,0.04669391,0.1270215,0.005289597,0.7058115,0.000226412,0.03578659],"study_design_scores_gemma":[0.00005260924,0.00001304248,0.0108549,0.00001013819,0.00002041652,0.000005450245,0.00005200361,0.986647,0.001000221,0.001258743,0.000009254843,0.00007625923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4272581,0.000009309796,0.5723685,0.0000379757,0.00002997679,0.0000250004,2.57822e-7,0.00006761232,0.0002032592],"genre_scores_gemma":[0.7745593,0.000002474869,0.2253345,0.00007952357,0.000006454099,8.038032e-7,5.938219e-7,0.000001594995,0.00001472471],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8596255,"threshold_uncertainty_score":0.2569304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07359833210321999,"score_gpt":0.3195067762571025,"score_spread":0.2459084441538825,"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."}}