{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006781374,0.002045936,0.001565167,0.006678203,0.0020896,0.003009086,0.003140175,0.001802232,0.005074629],"category_scores_gemma":[0.03873648,0.00196655,0.003750249,0.001719921,0.003094235,0.004993961,0.003494454,0.00266028,0.001564656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002883858,"about_ca_system_score_gemma":0.006030006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01248713,"about_ca_topic_score_gemma":0.01823156,"domain_scores_codex":[0.9881651,0.003073578,0.0008598301,0.001926584,0.005026465,0.0009483882],"domain_scores_gemma":[0.9668742,0.01937469,0.002344199,0.005376242,0.005777952,0.0002527007],"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":[0.0006873355,0.0004454996,0.01560401,0.001184736,0.0005017794,0.002009734,0.002202849,0.1693029,0.06492281,0.2637406,0.01296018,0.4664375],"study_design_scores_gemma":[0.0001289018,0.0001309159,0.001336669,0.0002371916,0.0002626324,0.0003586802,0.0002585633,0.7402803,0.08690936,0.154434,0.01550209,0.0001606794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01436573,0.00007031643,0.9719284,0.0001819361,0.00004759835,0.0001338548,0.0003339129,0.01132115,0.001617155],"genre_scores_gemma":[0.2175905,0.0002210217,0.77667,0.0002431617,0.0000840681,0.0002701093,0.001798239,0.001612106,0.00151077],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01248713,"threshold_uncertainty_score":0.03586376,"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."}}