{"id":"W4232351578","doi":"10.1145/1168918.1168908","title":"A probabilistic pointer analysis for speculative optimizations","year":2006,"lang":"en","type":"article","venue":"ACM SIGPLAN Notices","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Pointer analysis; Computer science; Pointer (user interface); Abstract interpretation; Optimizing compiler; Compiler; Correctness; Probabilistic logic; Test suite; Static analysis; Theoretical computer science; Algorithm; Program analysis; Programming language; Parallel computing; Test case; Artificial intelligence","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":[0.0001729411,0.0001287087,0.0001925398,0.0002551866,0.0001617212,0.0002213371,0.0008594355,0.00004754724,0.00001723831],"category_scores_gemma":[0.0002240246,0.0001162798,0.0001270365,0.0008248682,0.00003665499,0.0002606082,0.0001654472,0.00005037496,0.000009628323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002803693,"about_ca_system_score_gemma":0.00002841542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007072659,"about_ca_topic_score_gemma":0.00005978493,"domain_scores_codex":[0.9989868,0.00004799673,0.0002526736,0.0003621262,0.0001391322,0.0002112471],"domain_scores_gemma":[0.9986033,0.0004288439,0.0001484494,0.0006058813,0.0001728984,0.00004056458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006009104,0.00007495496,0.002258647,0.00001150595,0.0001060534,0.000002159803,0.0002083699,0.9318762,0.00001267046,0.0625286,0.002632383,0.0002824889],"study_design_scores_gemma":[0.0002242983,0.00005381461,0.004335924,0.000008929515,0.0001070853,0.000001072767,0.000007446651,0.9744432,0.0002848238,0.01951372,0.0008287256,0.0001909424],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003290951,0.00003865282,0.9918301,0.0008037616,0.00006612877,0.0002683737,0.00001238786,0.0004433085,0.003246346],"genre_scores_gemma":[0.4931404,9.313865e-7,0.506248,0.0001039585,0.00004775646,0.00002638531,0.00004744765,0.00000553375,0.0003795936],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4898494,"threshold_uncertainty_score":0.4741754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02183191752815897,"score_gpt":0.2729642003128487,"score_spread":0.2511322827846897,"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."}}