{"id":"W4405935701","doi":"10.23919/cnsm62983.2024.10814481","title":"Network Digital Twin for IGP Weight Optimization Demo","year":2024,"lang":"en","type":"article","venue":"","topic":"Industrial Technology and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ciena (Canada); Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009219044,0.0008018994,0.0003211676,0.0005843238,0.0005515045,0.001053992,0.0008154503,0.0005743494,0.04406127],"category_scores_gemma":[0.001697225,0.0003519403,0.000505538,0.0002862702,0.0005228305,0.001641513,0.00151829,0.001455609,0.003406764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007828622,"about_ca_system_score_gemma":0.0006575111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002479591,"about_ca_topic_score_gemma":0.004284301,"domain_scores_codex":[0.9996804,0.00006879671,0.00001018948,0.00003618189,0.0001667195,0.00003772859],"domain_scores_gemma":[0.999514,0.000116151,0.00001472649,0.0001515243,0.0001209677,0.00008263769],"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":[0.001706827,0.0005680344,0.004009948,0.0003090895,0.000108418,0.001293263,0.0008124682,0.3644733,0.03863075,0.1320639,0.204333,0.251691],"study_design_scores_gemma":[0.0001938808,0.0002658356,0.0008569845,0.00003762689,0.00002649155,0.0002799423,0.0001143252,0.8038661,0.01960875,0.02746499,0.1472387,0.00004621685],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08333738,0.0002142192,0.6962585,0.001954209,0.0008836282,0.000485379,0.002734941,0.03130184,0.1828299],"genre_scores_gemma":[0.4697622,0.0004166029,0.4516628,0.0005456213,0.0001296806,0.0006116441,0.004887877,0.005117108,0.06686646],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04406127,"threshold_uncertainty_score":0.1473997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008106507874212748,"score_gpt":0.1885276567275953,"score_spread":0.1804211488533826,"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."}}