{"id":"W3101831470","doi":"10.1051/epjconf/202024507025","title":"Using Kubernetes as an ATLAS computing site","year":2020,"lang":"en","type":"article","venue":"EPJ Web of Conferences","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Western Canada Research Grid; Compute Canada; U.S. Department of Energy; Science and Technology Facilities Council; National Science Foundation","keywords":"Cloud computing; Computer science; Large Hadron Collider; Software deployment; Operating system; Atlas (anatomy); Software; Grid computing; Grid; Software engineering; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002588577,0.0001649628,0.0003156515,0.00005291885,0.0001054708,0.0002584223,0.001047666,0.00006195569,0.00003791098],"category_scores_gemma":[0.00006274175,0.0001504224,0.00007201375,0.0003672794,0.00007052122,0.0003114521,0.0002460647,0.0001202209,0.00006284601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007947171,"about_ca_system_score_gemma":0.0005773841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000303104,"about_ca_topic_score_gemma":0.000009551588,"domain_scores_codex":[0.9984761,0.0001468581,0.0003749884,0.0004015393,0.0003334352,0.0002671155],"domain_scores_gemma":[0.9989949,0.0001321325,0.0002514919,0.0002854553,0.000155568,0.0001804599],"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":[0.0000434528,0.000222547,0.1356319,0.0003003908,0.0001836602,0.00007825489,0.01387002,0.03024848,0.01666245,0.7691609,0.002037444,0.0315605],"study_design_scores_gemma":[0.0002552775,0.0002544466,0.001693045,0.00009565276,0.00000818325,0.0000133101,0.0001469422,0.9854254,0.001466394,0.001485071,0.008917296,0.0002389427],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.767983,0.0001568228,0.2143551,0.0004738317,0.0003233901,0.0001066419,0.000006819319,0.0002164101,0.01637801],"genre_scores_gemma":[0.98972,0.000002790063,0.009832361,0.0002077443,0.0001991294,4.508511e-7,0.000009364217,0.000005811809,0.00002234413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9551769,"threshold_uncertainty_score":0.6134047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0676156731249819,"score_gpt":0.2961220769085214,"score_spread":0.2285064037835395,"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."}}