{"id":"W4226223886","doi":"10.1109/tsusc.2022.3165016","title":"Situation-Aware Orchestration of Resource Allocation and Task Scheduling for Collaborative Rendering in IoT Visualization","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Computing","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Distributed computing; Scheduling (production processes); Rendering (computer graphics); Orchestration; Quality of service; Visualization; Real-time computing; Computer network; Artificial intelligence","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":[0.00108182,0.0001520411,0.0002001573,0.0004987374,0.0009720439,0.0001161362,0.0002467971,0.00005349666,0.000001144613],"category_scores_gemma":[0.00003991535,0.0001938675,0.00004353279,0.001562763,0.00002911488,0.0003019127,0.00002281671,0.0002162079,2.27009e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003417925,"about_ca_system_score_gemma":0.0002638437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006540595,"about_ca_topic_score_gemma":0.00000565457,"domain_scores_codex":[0.998296,0.0002107458,0.0004530493,0.0004250169,0.0002752745,0.0003399704],"domain_scores_gemma":[0.9987586,0.0004219014,0.0002400909,0.0002100553,0.0003239233,0.00004547833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004534151,0.0001192493,0.00005942663,0.0001659111,0.00001609951,0.000003825438,0.01103346,0.9560736,0.001120881,0.004563166,0.00002957671,0.02676949],"study_design_scores_gemma":[0.00068851,0.000234619,0.00016097,0.00005260065,0.000009893614,0.000006408568,0.007707252,0.9844133,0.005424628,0.0007114197,0.0003960783,0.0001943503],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1444189,0.00004767843,0.8541322,0.0002299256,0.0004734906,0.0005390627,9.913405e-7,0.00009288974,0.00006481679],"genre_scores_gemma":[0.9832884,0.000002509503,0.01641108,0.00005510625,0.00009358839,0.00005531722,0.000009182949,0.00001724928,0.00006754143],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8388695,"threshold_uncertainty_score":0.7905688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01882454894156649,"score_gpt":0.2698118139673136,"score_spread":0.2509872650257471,"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."}}