{"id":"W1985281299","doi":"10.1109/broadnets.2008.4769065","title":"Survivable traffic grooming for scheduled demands","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Traffic grooming; Computer science; Computer network; Network topology; Distributed computing; Integer programming; Path protection; Routing (electronic design automation); Linear programming; Set (abstract data type); Throughput; Path (computing); Wavelength-division multiplexing; Telecommunications","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":[0.00004230549,0.00009991555,0.0001363075,0.00004102927,0.00007147996,0.000005871758,0.0001130457,0.0000863699,0.00003235679],"category_scores_gemma":[0.00005494816,0.0000915277,0.0000423455,0.0001368481,0.00004319515,0.00009713531,0.00001821431,0.00008746887,0.00001983942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002613435,"about_ca_system_score_gemma":0.000003672923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.829739e-7,"about_ca_topic_score_gemma":0.000005286285,"domain_scores_codex":[0.9994329,0.000001807016,0.0001226991,0.0001108793,0.00005259378,0.0002791685],"domain_scores_gemma":[0.9996786,0.0001134093,0.000006881144,0.0001502265,0.00001746487,0.00003342349],"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":[0.00001298217,0.0000227748,0.0003206636,0.00005975254,0.00004268748,0.000009040602,0.00003171678,0.9587647,0.00165654,0.01345469,0.003778707,0.02184578],"study_design_scores_gemma":[0.0006087744,0.00005426207,0.0002320155,0.00001309083,0.000008414206,0.00001731653,0.0000973654,0.9799272,0.005828961,0.001957724,0.0109266,0.0003282456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5424122,0.0003066559,0.4496366,0.00004393702,0.0001227538,0.0001624602,0.00000108618,0.002606711,0.004707602],"genre_scores_gemma":[0.7275459,0.00008371598,0.2719236,0.00001248203,0.00003927835,0.00003733459,0.000002178212,0.00002409677,0.0003314383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1851337,"threshold_uncertainty_score":0.3732391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0192826818611258,"score_gpt":0.2163690304560027,"score_spread":0.1970863485948769,"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."}}