{"id":"W2110062978","doi":"10.1109/cnsr.2011.34","title":"Adaptive Load Balancing for the Agile All-Photonic Network","year":2011,"lang":"en","type":"article","venue":"","topic":"Optical Network Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Computer network; Load balancing (electrical power); Distributed computing; Network packet; Edge device; The Internet; Scheduling (production processes); Cloud computing; Engineering; Operating system","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":[0.0001432144,0.000115567,0.0001137022,0.00001116721,0.00005417526,0.00001334882,0.0002548755,0.00009149586,0.0001617026],"category_scores_gemma":[0.00003153396,0.00007588763,0.00005717043,0.0001163022,0.00005052775,0.00005436912,0.00005985456,0.0001481161,0.00007198226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005940396,"about_ca_system_score_gemma":0.000008236733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001875343,"about_ca_topic_score_gemma":0.00007752325,"domain_scores_codex":[0.9992998,0.000003964733,0.0001205362,0.0001159474,0.00007497228,0.0003847567],"domain_scores_gemma":[0.9994286,0.0002277057,0.00001178508,0.0002750993,0.00002820115,0.00002863238],"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":[0.0001086331,0.00005696006,0.0007839208,0.00007179067,0.0009270043,0.00001459563,0.000899332,0.2273428,0.0006814392,0.400052,0.2711145,0.09794705],"study_design_scores_gemma":[0.0002405967,0.0001150078,0.0007763713,0.00002477622,0.00005236996,0.000003781535,0.0003074167,0.9446724,0.002699899,0.01417217,0.0366482,0.0002870209],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04704734,0.007816055,0.5267057,0.0004715522,0.002812073,0.002406718,0.00001173249,0.00928466,0.4034442],"genre_scores_gemma":[0.9237255,0.0001467915,0.07544269,0.0001398355,0.0001226843,0.0001179277,7.41425e-7,0.00003218104,0.0002715896],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8766782,"threshold_uncertainty_score":0.3094608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03197601850705388,"score_gpt":0.2103220289175221,"score_spread":0.1783460104104682,"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."}}