{"id":"W2115500558","doi":"10.1109/ccgrid.2007.111","title":"Study of Different Replica Placement and Maintenance Strategies in Data Grid","year":2007,"lang":"en","type":"article","venue":"","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Replica; Computer science; Latency (audio); Replication (statistics); Cache; Data center; Distributed computing; Grid; Performance metric; Data grid; Metric (unit); Grid computing; Data access; Response time; Parallel computing; Computer network; Real-time computing; Operating system; Database; Engineering","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":[0.002564304,0.0005720984,0.0008615584,0.0008900405,0.0005760608,0.00113646,0.001388153,0.0009288556,0.0005556568],"category_scores_gemma":[0.01033991,0.0003818304,0.0004876419,0.00134824,0.0006085218,0.001913435,0.0003236336,0.0004449927,0.0001236472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001314583,"about_ca_system_score_gemma":0.0008257661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003395309,"about_ca_topic_score_gemma":0.002281614,"domain_scores_codex":[0.9984989,0.0006628636,0.00007925728,0.0002250224,0.0003666088,0.0001673527],"domain_scores_gemma":[0.9950011,0.003134067,0.0004818885,0.0004295546,0.0007885655,0.0001647211],"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":[0.0002905192,0.0001640744,0.006625882,0.0002535162,0.0001364522,0.0001793748,0.0002165114,0.8535934,0.01062271,0.01813047,0.0008703945,0.1089168],"study_design_scores_gemma":[0.00002412482,0.0001816866,0.00112231,0.000009785104,0.00004032745,0.0001594832,0.00009897668,0.9917635,0.002952892,0.002906225,0.0007301017,0.0000106212],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5000821,0.005385974,0.4867339,0.0009198205,0.00009560944,0.0002074413,0.00008769784,0.0003934159,0.006094138],"genre_scores_gemma":[0.9503474,0.0007706009,0.04797766,0.0000338963,0.00002417175,0.00005266214,0.00003332357,0.00002826236,0.0007320467],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003395309,"threshold_uncertainty_score":0.01356155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04560999353704979,"score_gpt":0.3038955860644414,"score_spread":0.2582855925273916,"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."}}