{"id":"W2116451280","doi":"10.1109/icns.2006.15","title":"A Scalable Wide-Area Grid Resource Management Framework","year":2006,"lang":"en","type":"article","venue":"","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Regina","funders":"","keywords":"Computer science; Scalability; Distributed computing; Grid; Grid computing; Semantic grid; Resource management (computing); Quality of service; DRMAA; Resource (disambiguation); Overhead (engineering); Resource allocation; Database; Computer network; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00223599,0.0005594954,0.0006659587,0.0008305332,0.001364254,0.002319811,0.002734369,0.001121699,0.002384062],"category_scores_gemma":[0.001600422,0.0004165044,0.0007498076,0.0009988986,0.0007551256,0.002536342,0.002303646,0.001222148,0.001037399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001351248,"about_ca_system_score_gemma":0.003589072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01111934,"about_ca_topic_score_gemma":0.01233345,"domain_scores_codex":[0.9989048,0.000183221,0.00008086877,0.0001165159,0.0005613989,0.0001530945],"domain_scores_gemma":[0.9994631,0.00007677302,0.000041269,0.000110738,0.0001660019,0.0001421569],"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":[0.0002145029,0.0002839456,0.00144237,0.0003504668,0.000136052,0.001028712,0.0004599925,0.2698334,0.01465651,0.3247126,0.08901968,0.2978618],"study_design_scores_gemma":[0.0001071507,0.00007447811,0.0003823288,0.00005626414,0.00004275573,0.0002338159,0.00007597068,0.8074,0.002445303,0.05953234,0.1295813,0.00006827656],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0060609,0.0008526279,0.9655687,0.001177514,0.0001600525,0.0004376359,0.000364742,0.0125162,0.01286162],"genre_scores_gemma":[0.1465309,0.001031743,0.8415024,0.0004636612,0.0001535952,0.0006970157,0.001784353,0.0004484521,0.007387927],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01111934,"threshold_uncertainty_score":0.02210921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00928870016891063,"score_gpt":0.2097595045333648,"score_spread":0.2004708043644542,"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."}}