{"id":"W2107345347","doi":"10.1109/icccn.2007.4317809","title":"Grid Computing on Massively Multi-User Online Platform","year":2007,"lang":"en","type":"article","venue":"","topic":"Peer-to-Peer Network Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Massively parallel; Grid computing; Scalability; Distributed computing; Flexibility (engineering); Grid; Data-intensive computing; End-user computing; Utility computing; Supercomputer; Architecture; Computer cluster; Cloud computing; Parallel computing; Operating system","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":[0.000438119,0.0002027552,0.0001879677,0.0002803129,0.0001146296,0.0001068449,0.001644417,0.0001231565,0.000008433485],"category_scores_gemma":[0.0001132167,0.0001684657,0.00005664878,0.0007495025,0.00004269264,0.0002430041,0.0009170495,0.000300063,0.0002872189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001039073,"about_ca_system_score_gemma":0.00002558466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000335424,"about_ca_topic_score_gemma":0.0001667581,"domain_scores_codex":[0.9981937,0.000007781459,0.0003018211,0.0004992384,0.0003597871,0.0006376423],"domain_scores_gemma":[0.9987558,0.0002082637,0.00008069533,0.0007329467,0.00008763776,0.0001347057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002605383,0.0004900178,0.004761706,0.00001066394,0.0000414261,0.0002601486,0.0005193238,0.003926117,0.001286933,0.1908392,0.04082961,0.7570087],"study_design_scores_gemma":[0.002828532,0.001217186,0.2740812,0.0002381756,0.0000129995,0.0001230878,0.0006953338,0.389852,0.05937381,0.003339938,0.2660233,0.002214486],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1349636,0.00001604583,0.85639,0.002627466,0.0007029204,0.0001775643,0.000002884157,0.001886696,0.003232844],"genre_scores_gemma":[0.3955184,0.000001762846,0.6002229,0.002383603,0.0001615691,0.00000132201,0.000003346674,0.00001192854,0.001695153],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7547943,"threshold_uncertainty_score":0.6869833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04071652320563771,"score_gpt":0.298007846829855,"score_spread":0.2572913236242172,"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."}}