{"id":"W1992506382","doi":"10.1016/j.future.2006.12.006","title":"GridX1: A Canadian computational grid","year":2007,"lang":"en","type":"article","venue":"Future Generation Computer Systems","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University; University of Toronto; TRIUMF; Canarie; National Research Council Canada; University of Alberta; University of Calgary; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; CERN","keywords":"Computer science; Grid; Grid computing; Distributed computing; Job scheduler; Load balancing (electrical power); Fault tolerance; Scheduling (production processes); Overhead (engineering); Computer cluster; Large Hadron Collider; Database; Operating system; Cloud computing","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001909868,0.001120972,0.001008204,0.00283426,0.004924664,0.003720056,0.003621243,0.0009474358,0.0659615],"category_scores_gemma":[0.005539389,0.0006363013,0.0008779265,0.006812483,0.001370521,0.002813287,0.003148977,0.001971904,0.01281441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02262909,"about_ca_system_score_gemma":0.07154386,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9021534,"about_ca_topic_score_gemma":0.8798738,"domain_scores_codex":[0.9983804,0.0001495283,0.00004177041,0.0001787175,0.0008090047,0.0004406421],"domain_scores_gemma":[0.994621,0.0001978077,0.0001018658,0.0004640972,0.003307202,0.001308006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004254828,0.00005967947,0.002254886,0.0001505509,0.0000285928,0.00008039011,0.0001906124,0.01455274,0.001083128,0.07699635,0.850161,0.05401655],"study_design_scores_gemma":[0.0002131863,0.00002985322,0.002546594,0.00005175942,0.00002780559,0.00004916235,0.0002100337,0.02968471,0.001275292,0.01173551,0.9541004,0.00007569908],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.03422562,0.002707436,0.1201181,0.02105455,0.004252888,0.001359825,0.158559,0.07020319,0.5875194],"genre_scores_gemma":[0.2565288,0.004038764,0.2306994,0.002201228,0.000505935,0.001052567,0.1936855,0.01430292,0.2969849],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.09784663,"threshold_uncertainty_score":0.2206632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.014340742692549,"score_gpt":0.2223005355617464,"score_spread":0.2079597928691974,"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."}}