{"id":"W2129923823","doi":"10.4304/jcm.7.5.400-408","title":"Downstream-based Scheduling for Energy Conservation in Green EPONs","year":2012,"lang":"en","type":"article","venue":"Journal of Communications","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology; University of Waterloo","funders":"","keywords":"Computer science; Environmental science; Energy conservation; Scheduling (production processes); Ecology; Mathematics; Mathematical optimization; Biology","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":[0.0002169787,0.00006258382,0.0001275457,0.0001473871,0.00004621477,0.00000792571,0.0003821887,0.00006526987,0.000002692662],"category_scores_gemma":[0.0001747379,0.00006083409,0.00005100348,0.0002109858,0.00006006642,0.0002379112,0.00003556403,0.0002037944,9.599262e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007894742,"about_ca_system_score_gemma":0.00002111038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005493614,"about_ca_topic_score_gemma":0.00004930087,"domain_scores_codex":[0.9994167,0.00002299492,0.000324229,0.00002403539,0.00006111695,0.0001508919],"domain_scores_gemma":[0.9988394,0.0005478811,0.00009361673,0.0003879643,0.00009058131,0.00004059877],"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":[0.00006373641,0.0004910158,0.02091355,0.00008176336,0.0001409565,0.000001650539,0.000267018,0.5154485,0.006843421,0.3356344,0.001020121,0.1190938],"study_design_scores_gemma":[0.001656962,0.0001197754,0.00884604,0.0003135709,0.00007221135,0.00003125523,0.000459582,0.8585063,0.00372651,0.03755045,0.0883405,0.0003768564],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07544874,0.006854319,0.9094079,0.005963607,0.0001993104,0.0001418569,0.000007793351,0.0001730292,0.001803502],"genre_scores_gemma":[0.6779979,0.0002672247,0.3216176,0.0000557713,0.00003123134,0.00001311442,0.000003778122,0.000009199264,0.000004134043],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6025493,"threshold_uncertainty_score":0.2480742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03436517072594063,"score_gpt":0.2809146160056933,"score_spread":0.2465494452797526,"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."}}