{"id":"W3163215105","doi":"","title":"IDEal: Efficient and Precise Alias-Aware Dataflow Analysis","year":2017,"lang":"en","type":"article","venue":"Conference on Object-Oriented Programming Systems, Languages, and Applications","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Alias; Computer science; Dataflow; Aliasing; Ideal (ethics); Programming language; Static analysis; Theoretical computer science; Parallel computing; Algorithm; Data mining; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004372999,0.001250891,0.0010075,0.002369327,0.0009749109,0.003115725,0.003919661,0.001055955,0.003385263],"category_scores_gemma":[0.01300361,0.001167695,0.002028818,0.001551752,0.002322357,0.007456623,0.003925375,0.002824889,0.001651899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002065672,"about_ca_system_score_gemma":0.00557475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005928815,"about_ca_topic_score_gemma":0.007866551,"domain_scores_codex":[0.9936098,0.0008566426,0.00043181,0.0008924502,0.003680713,0.0005285739],"domain_scores_gemma":[0.9930412,0.002299949,0.000579473,0.002580769,0.00126145,0.0002372143],"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":[0.001684698,0.0004714521,0.01900417,0.001421799,0.0002919364,0.0002819005,0.001222037,0.08573496,0.04800354,0.1134651,0.06786419,0.6605542],"study_design_scores_gemma":[0.0002139347,0.0002390327,0.002434304,0.0001856727,0.0001828335,0.0003130716,0.0002365594,0.7638357,0.07716659,0.07570786,0.07931118,0.0001733635],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01289703,0.0004843048,0.905076,0.0003795399,0.00007938179,0.000129684,0.0009143208,0.07672689,0.003312938],"genre_scores_gemma":[0.1762855,0.0004628529,0.8104091,0.0004697693,0.0001009837,0.0002075199,0.002765743,0.006394407,0.002904206],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005928815,"threshold_uncertainty_score":0.0231269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0240224567873954,"score_gpt":0.3197320523337395,"score_spread":0.2957095955463441,"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."}}