{"id":"W2130550680","doi":"10.1007/978-3-642-14295-6_43","title":"Abstract Analysis of Symbolic Executions","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Symbolic execution; Matching (statistics); Programming language; Theoretical computer science; Symbolic data analysis; Model checking; Software; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00141526,0.0003686424,0.0006697908,0.00256698,0.0001809723,0.0002176416,0.003891388,0.0004242206,0.00005571579],"category_scores_gemma":[0.0001972224,0.0003488878,0.0002800438,0.002391889,0.0009607082,0.0005733013,0.0007683526,0.0009788993,0.00002347462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001461813,"about_ca_system_score_gemma":0.0004068518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004236177,"about_ca_topic_score_gemma":0.0000959304,"domain_scores_codex":[0.9967569,0.00002785896,0.0006987624,0.00112815,0.0009431478,0.0004451572],"domain_scores_gemma":[0.9962907,0.000397512,0.0005528016,0.002257114,0.0003637695,0.0001380873],"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":[0.000004372197,0.00006948686,0.0001567232,0.00005140325,0.0001594508,0.00001853037,0.001268816,0.04016384,0.005774603,0.2763461,0.000004313936,0.6759824],"study_design_scores_gemma":[0.0001555689,0.0001007827,0.01203407,0.0001839961,0.0001791794,0.00002074285,1.812541e-7,0.8215393,0.01862364,0.1450601,0.001232236,0.0008702016],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004582608,0.0001269928,0.9914242,0.0001390708,0.001409095,0.0002158775,0.00001188019,0.0001023664,0.006112278],"genre_scores_gemma":[0.1593895,0.00002646684,0.840146,0.0002032066,0.0001212605,0.000005938002,0.000007116817,0.00001503178,0.00008550179],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7813755,"threshold_uncertainty_score":0.9998963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0242290981888959,"score_gpt":0.2909268837353042,"score_spread":0.2666977855464083,"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."}}