{"id":"W1992299932","doi":"10.1109/iscc.2012.6249289","title":"Greening the multi-granular optical transport network design under the optical reach constraint","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Bottleneck; Traffic grooming; Optical Transport Network; Network planning and design; Energy consumption; Heuristics; Routing and wavelength assignment; Computer network; Backbone network; Bandwidth (computing); Wavelength-division multiplexing; Distributed computing; Electronic engineering; Optical performance monitoring; Engineering; Wavelength; Embedded system; Electrical engineering; Optics","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":[0.0007172042,0.0002937097,0.000255346,0.00002236988,0.0002207382,0.0000302771,0.0004838428,0.0002419017,0.00007184],"category_scores_gemma":[0.00005812713,0.0001572633,0.0001172263,0.0002981354,0.0007424919,0.0001608307,0.00006459953,0.0008337676,0.00006493576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005720564,"about_ca_system_score_gemma":0.00001102159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002270913,"about_ca_topic_score_gemma":0.00001270909,"domain_scores_codex":[0.9981181,0.0000443404,0.0003433145,0.0002017984,0.0002526591,0.001039761],"domain_scores_gemma":[0.9983708,0.0008800942,0.00001953658,0.0005549843,0.00002707088,0.0001475583],"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":[0.00001273846,0.00003347409,0.0006647556,0.000007242943,0.00007108525,0.000008534829,0.00007342218,0.7560285,0.0002783625,0.2315441,0.000491859,0.01078593],"study_design_scores_gemma":[0.001399556,0.0001503557,0.01935209,0.0001084292,0.0003777523,0.0003115865,0.002878567,0.9428168,0.003400111,0.01561756,0.01195808,0.001629104],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005923927,0.001099535,0.9860417,0.0009599203,0.0002954445,0.0004308275,9.596398e-7,0.001314376,0.003933278],"genre_scores_gemma":[0.6286263,0.00005730925,0.370812,0.0001686825,0.0002064642,0.00004507568,0.000001927538,0.00004002071,0.00004220818],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6227024,"threshold_uncertainty_score":0.6413012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03606268766976606,"score_gpt":0.2438970816489615,"score_spread":0.2078343939791954,"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."}}