{"id":"W2096780974","doi":"10.1109/ipdps.2005.277","title":"Measuring Scalability of Resource Management Systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Manitoba","funders":"","keywords":"Scalability; Metric (unit); Overhead (engineering); Computer science; Distributed computing; Resource (disambiguation); Grid; Resource management (computing); Performance metric; Resource Management System; Resource allocation; Computer network; Engineering; Database; Operating system; 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":[],"consensus_categories":[],"category_scores_codex":[0.0007515797,0.00008778453,0.0001578775,0.00005774339,0.00005040795,0.00008166531,0.0007766132,0.00002985004,0.000004579679],"category_scores_gemma":[0.000007518597,0.00007492631,0.00005424112,0.0002627914,0.00001926318,0.0001313777,0.0002377549,0.00004845982,0.00005712044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004275402,"about_ca_system_score_gemma":0.00001041408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003568167,"about_ca_topic_score_gemma":0.00000175705,"domain_scores_codex":[0.9987953,0.00009247049,0.0003279933,0.0002676898,0.0003196415,0.0001969397],"domain_scores_gemma":[0.9990994,0.00004589232,0.00008872643,0.0006486652,0.00005590563,0.00006145373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001036624,0.0003290834,0.005340214,0.0006281811,0.0001232191,0.00001102954,0.0008075272,0.19954,0.0001704067,0.6918932,0.01466838,0.08647832],"study_design_scores_gemma":[0.0007120481,0.00006819219,0.01009994,0.0002548496,0.0000122311,0.00003306476,0.0002080874,0.6262956,0.000756517,0.0003937765,0.3607417,0.0004239829],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01714373,0.0001908632,0.8217872,0.0002289735,0.0001944706,0.0001863893,0.000001176583,0.0002358741,0.1600313],"genre_scores_gemma":[0.9860465,0.000001075713,0.01237934,0.00002944766,0.00006430205,0.000004996093,9.69448e-7,0.000003309814,0.001470092],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9689028,"threshold_uncertainty_score":0.3055407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02781545751044491,"score_gpt":0.2216633641960048,"score_spread":0.1938479066855599,"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."}}