{"id":"W1583055368","doi":"10.1007/978-3-540-24644-2_26","title":"To Inline or Not to Inline? Enhanced Inlining Decisions","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Institute of Computing Technology, Chinese Academy of Sciences","keywords":"Heuristics; Computer science; Compiler; Suite; Adaptation (eye); Parallel computing; Speedup; Programming language; Operating system","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":[0.001758915,0.0008199504,0.0005749454,0.0005367947,0.0007579416,0.002206443,0.0009383373,0.0008976844,0.02797726],"category_scores_gemma":[0.01555395,0.0003869193,0.000357998,0.0005564688,0.0004628506,0.004713533,0.0009185243,0.001115171,0.004216939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004155952,"about_ca_system_score_gemma":0.0005748007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004906452,"about_ca_topic_score_gemma":0.001507377,"domain_scores_codex":[0.998513,0.000523987,0.00009373935,0.000270854,0.0003586799,0.0002396411],"domain_scores_gemma":[0.9932292,0.003627937,0.0004359227,0.001579795,0.0007894176,0.0003377312],"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":[0.002409343,0.0003761529,0.004091752,0.0002657907,0.00005495085,0.0005494737,0.0006194229,0.02810546,0.01842114,0.1205821,0.06710583,0.7574185],"study_design_scores_gemma":[0.0003827392,0.00111386,0.003451468,0.0003161134,0.000207842,0.001022597,0.000816462,0.4551355,0.06819829,0.2958254,0.1733952,0.000134654],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.278414,0.001452967,0.4956219,0.007182518,0.00178575,0.0002336184,0.000665957,0.009749017,0.2048943],"genre_scores_gemma":[0.8006356,0.0004398778,0.1552775,0.0009079802,0.0004252506,0.00007653434,0.00042121,0.002609319,0.03920665],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02797726,"threshold_uncertainty_score":0.09359324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03387683455929914,"score_gpt":0.3127567003453888,"score_spread":0.2788798657860897,"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."}}