{"id":"W2134616020","doi":"10.1109/icdcs.2010.60","title":"Resource Allocation with Supply Adjustment in Distributed Computing Systems","year":2010,"lang":"en","type":"article","venue":"","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Resource allocation; Grid computing; Grid; Distributed computing; Profit (economics); Resource management (computing); Shared resource; Supply and demand; Resource (disambiguation); Point (geometry); Microeconomics; Computer network; Economics","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":[0.0006026567,0.0001866481,0.0002299402,0.0001106418,0.0001020582,0.0002902164,0.0008369328,0.0000888011,0.000004814217],"category_scores_gemma":[0.00002286806,0.0001464594,0.00003155975,0.0006611901,0.00003378511,0.0002077413,0.0001614285,0.0002931238,0.00003982932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006343933,"about_ca_system_score_gemma":0.00007763457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004066316,"about_ca_topic_score_gemma":0.0001279976,"domain_scores_codex":[0.9982809,0.0001087416,0.0003835876,0.0004686,0.0003496733,0.0004084335],"domain_scores_gemma":[0.9988548,0.0001315181,0.0001433398,0.000648992,0.00009932199,0.0001220004],"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":[0.00004632683,0.0005988554,0.05668566,0.0001902473,0.00008161433,0.0001162066,0.002361275,0.3036665,0.002164392,0.5950603,0.01933243,0.01969615],"study_design_scores_gemma":[0.0009317258,0.0001213577,0.04565147,0.0001474046,0.000004581006,0.0001440823,0.0001790746,0.9165707,0.0001236515,0.00007691165,0.03566056,0.0003884335],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1305576,0.00006306119,0.8633457,0.0007145169,0.0006642219,0.0003832248,0.000008177146,0.0003907227,0.003872692],"genre_scores_gemma":[0.9926766,6.23631e-7,0.006791101,0.00009064482,0.0001442144,0.00001242599,0.00008621287,0.000009514136,0.00018863],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.862119,"threshold_uncertainty_score":0.5972441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008038435799160717,"score_gpt":0.2178359503598735,"score_spread":0.2097975145607127,"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."}}