{"id":"W4255874599","doi":"10.1145/3262847","title":"Session details: Runtime optimization and profiling","year":2006,"lang":"en","type":"article","venue":"ACM SIGPLAN Notices","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Profiling (computer programming); Session (web analytics); Programming language; World Wide Web","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":[0.0002221191,0.0001107621,0.0001236241,0.00005669039,0.0001593643,0.0003347819,0.0005474698,0.00005522216,0.000004544343],"category_scores_gemma":[0.00005255341,0.00009473562,0.00002051151,0.0001927551,0.00002005176,0.0003959799,0.00022066,0.00006559359,0.00002319267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001021567,"about_ca_system_score_gemma":0.00002144155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008241077,"about_ca_topic_score_gemma":0.000005387072,"domain_scores_codex":[0.9990905,0.00005984154,0.0001941134,0.0002896233,0.0001697978,0.0001961067],"domain_scores_gemma":[0.9992548,0.0001671061,0.00011808,0.0003695214,0.0000471395,0.00004339115],"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":[0.0000144255,0.0001477519,0.07156785,0.0002033722,0.00003527825,0.00005569743,0.0006055917,0.8825818,0.001988115,0.02870494,0.00358924,0.01050596],"study_design_scores_gemma":[0.0003040048,0.00004856434,0.004802575,0.00007904199,0.00001017,0.0000195547,0.00002898536,0.9906707,0.0009878071,0.001054866,0.001752221,0.0002414564],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1891685,0.0004707347,0.8055543,0.0004031387,0.0004049038,0.000177836,0.000005347517,0.0003477636,0.00346743],"genre_scores_gemma":[0.8855709,0.000002774615,0.1140687,0.00004624779,0.0001279932,0.000003013382,0.00003424964,0.000005467088,0.0001407033],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6964024,"threshold_uncertainty_score":0.3863207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0143290584619703,"score_gpt":0.2359297262563504,"score_spread":0.2216006677943801,"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."}}