{"id":"W2162856822","doi":"10.1109/icc.2008.36","title":"Use of Network Families in Survivable Network Design and Optimization","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Survivability; Computer science; Scheme (mathematics); Variety (cybernetics); Network planning and design; Telecommunications network; Distributed computing; Simple (philosophy); Computer network; Network simulation; Random graph; Network formation; Theoretical computer science; Mathematics; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003165237,0.0009057477,0.0005680282,0.001073236,0.001023661,0.001010063,0.000943133,0.000927544,0.001312504],"category_scores_gemma":[0.008392925,0.0006372529,0.0009037718,0.000926444,0.0017358,0.003465639,0.001326307,0.001360204,0.0002652617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009499988,"about_ca_system_score_gemma":0.000609334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002581218,"about_ca_topic_score_gemma":0.001756196,"domain_scores_codex":[0.9985852,0.0009811459,0.00005021718,0.0001125582,0.0002231159,0.00004779571],"domain_scores_gemma":[0.9956951,0.003204246,0.0003370092,0.0004095693,0.0002829916,0.00007110714],"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":[0.00003481039,0.0000244303,0.0007752303,0.00003774102,0.00002892319,0.00005549554,0.00009805046,0.8675019,0.0009181745,0.1122371,0.000334011,0.01795418],"study_design_scores_gemma":[0.000007359631,0.00004671158,0.0001140894,0.00002726167,0.0000109105,0.00004877907,0.0000231736,0.9252301,0.0008601741,0.06973161,0.003882907,0.00001695933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02020672,0.0004363293,0.9730733,0.0002613239,0.00003822843,0.00005144281,0.00005608828,0.0001765387,0.005699897],"genre_scores_gemma":[0.5813334,0.002086979,0.4130655,0.0001775929,0.0000782259,0.0003831158,0.0001330762,0.0002231069,0.002519019],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003165237,"threshold_uncertainty_score":0.01673955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02985026684496386,"score_gpt":0.2023883358975215,"score_spread":0.1725380690525576,"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."}}