{"id":"W4288079579","doi":"10.1145/3419111.3421299","title":"Semi-dynamic load balancing","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Stochastic Gradient Optimization Techniques","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Load balancing (electrical power); Sizing; Distributed computing; Software deployment; Python (programming language); Execution time; Synchronization (alternating current); Key (lock); Parallel computing; Operating system; Computer network","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016897,0.0002484408,0.0002741297,0.0001068327,0.00004891168,0.0002618918,0.001802587,0.0001915722,0.00004812095],"category_scores_gemma":[0.0001400575,0.0002457328,0.0001078947,0.0002657202,0.00002574945,0.0001302765,0.003105916,0.0004538429,0.00009940467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002475215,"about_ca_system_score_gemma":0.0003383614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003942815,"about_ca_topic_score_gemma":0.00000439761,"domain_scores_codex":[0.9981846,0.00003288813,0.0002987093,0.0007905966,0.0004506929,0.0002424647],"domain_scores_gemma":[0.9985126,0.0000609768,0.0001547367,0.0009775311,0.0001645069,0.0001297069],"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":[0.00001072001,0.000172799,0.0002652034,0.0006322524,0.0002339725,0.0001499182,0.00464406,0.05999704,0.001648046,0.8331971,0.06182002,0.03722888],"study_design_scores_gemma":[0.00006764023,0.00002293121,0.00006857836,0.00007473749,0.000006541777,0.000007140804,0.000005399111,0.9382932,0.0005342077,0.06025178,0.000379527,0.000288313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00005327727,0.00009648428,0.9772368,0.002664782,0.0007888619,0.0003401467,0.000003978568,0.002502964,0.01631267],"genre_scores_gemma":[0.1921351,0.00003142979,0.8059635,0.001073302,0.00005270585,0.0000653751,0.00001512463,0.00002333222,0.0006401294],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8782961,"threshold_uncertainty_score":0.9999995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01710817377559423,"score_gpt":0.2580077198261286,"score_spread":0.2408995460505344,"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."}}