{"id":"W2295677615","doi":"10.1109/itc.2014.6932974","title":"The GENI Experiment Engine","year":2014,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"University of Utah; National Science Foundation","keywords":"Testbed; Computer science; Gee; Simple (philosophy); Distributed computing; Computer network; Simulation; Generalized estimating equation","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":[0.005337929,0.001237934,0.0009701258,0.0007884894,0.0005923872,0.00251395,0.003928939,0.0008717087,0.02453265],"category_scores_gemma":[0.006785223,0.0009228425,0.0007987147,0.0007360812,0.0007869986,0.002944646,0.00380956,0.002449386,0.0164416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009148908,"about_ca_system_score_gemma":0.002131084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002217047,"about_ca_topic_score_gemma":0.002485855,"domain_scores_codex":[0.9969151,0.0009216074,0.0001663626,0.0005930873,0.001039219,0.0003644891],"domain_scores_gemma":[0.9964315,0.0008683282,0.0001754481,0.001579408,0.0005901692,0.0003551686],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.005360664,0.001606757,0.01390127,0.003504446,0.0005442877,0.001007185,0.001340791,0.04725465,0.09224109,0.1272656,0.429,0.2769732],"study_design_scores_gemma":[0.0005232996,0.000650898,0.004233516,0.0002158868,0.0001202256,0.0004537202,0.0001564778,0.08143779,0.03351229,0.03227689,0.846185,0.0002339602],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01607236,0.0009479492,0.6234699,0.001209795,0.0008608056,0.004461723,0.01631905,0.24804,0.08861847],"genre_scores_gemma":[0.1286381,0.001450186,0.7566473,0.00270626,0.0003034846,0.008123766,0.0390531,0.0341034,0.02897443],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02453265,"threshold_uncertainty_score":0.08206987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006893379910910241,"score_gpt":0.2082216281234382,"score_spread":0.2013282482125279,"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."}}