{"id":"W1849761680","doi":"","title":"Hierarchical optimization procedure for traffic grooming in WDM optical networks","year":2009,"lang":"en","type":"article","venue":"Optical Network Design and Modelling","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Traffic grooming; Wavelength-division multiplexing; Heuristic; Routing and wavelength assignment; Computer science; Network topology; Routing (electronic design automation); Multiplexing; Computer network; Topology (electrical circuits); Mesh networking; Mathematical optimization; Wavelength; Mathematics; Telecommunications; Optics; Artificial intelligence; Physics","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":[0.0004110823,0.0003627733,0.0004660146,0.0001028109,0.0001412372,0.00009137593,0.0001936637,0.0004743981,0.000003472821],"category_scores_gemma":[0.00007074117,0.0003604009,0.00007783512,0.0004310199,0.0001247151,0.0002144426,0.00003223357,0.0006814973,9.815058e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007202469,"about_ca_system_score_gemma":0.00001563712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":1.243059e-7,"about_ca_topic_score_gemma":8.93495e-7,"domain_scores_codex":[0.9977852,0.00002723514,0.0005114285,0.0004921803,0.0001583858,0.001025546],"domain_scores_gemma":[0.9988732,0.0006450647,0.00002132087,0.0002070529,0.00003860996,0.0002147318],"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":[0.0001319735,0.0000381441,0.000002845748,0.00002509095,0.00000979908,0.00001021741,0.00002323408,0.9389141,0.00003071556,0.02175924,0.00009055367,0.03896407],"study_design_scores_gemma":[0.0005945549,0.0002070046,0.000005763517,0.0001509738,0.00002779046,0.00001384324,0.00001518466,0.9887442,0.00002402873,0.009702978,0.00009516437,0.0004184991],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004438702,0.001918706,0.9914007,0.0002752013,0.0001256095,0.0008502316,5.361932e-7,0.0007261937,0.0002641612],"genre_scores_gemma":[0.3691356,0.0008053656,0.6296149,0.000080436,0.0002442793,0.00005992776,0.000008468332,0.000044324,0.000006663508],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3646969,"threshold_uncertainty_score":0.9998848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01744072078354426,"score_gpt":0.2209983212656173,"score_spread":0.203557600482073,"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."}}