{"id":"W2186630404","doi":"10.82308/2492","title":"Robust network design","year":2010,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"University of Pennsylvania","keywords":"Counterexample; Network planning and design; Mathematical optimization; Conjecture; Set (abstract data type); Computer science; Tree (set theory); Generality; Robustness (evolution); Routing (electronic design automation); Mathematics; Theoretical computer science; Discrete mathematics; Combinatorics","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":[0.001846322,0.001620925,0.001206985,0.001140169,0.000945383,0.003057677,0.002511478,0.002169562,0.01962334],"category_scores_gemma":[0.006802704,0.0005808909,0.001323329,0.001072307,0.001556491,0.003116735,0.002998526,0.002416642,0.005275473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002151561,"about_ca_system_score_gemma":0.001469999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001522137,"about_ca_topic_score_gemma":0.001380967,"domain_scores_codex":[0.9975805,0.0006102959,0.0001404204,0.0006597903,0.0007891394,0.0002197895],"domain_scores_gemma":[0.9975933,0.0008323728,0.0002830056,0.0006291942,0.0005700148,0.0000920259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001175464,0.00004490703,0.0003522829,0.0004137487,0.00009073485,0.0001881097,0.00007443017,0.3496908,0.004415233,0.4805299,0.01351946,0.1505628],"study_design_scores_gemma":[0.00003623827,0.000108079,0.0001255742,0.0001060574,0.00003670959,0.0002235209,0.00004372354,0.6311954,0.003123919,0.2900846,0.07487752,0.0000386541],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001413088,0.0006820522,0.9718407,0.0004651214,0.0002415742,0.0001118036,0.0002392134,0.0003882649,0.02461827],"genre_scores_gemma":[0.3505195,0.005313019,0.5848897,0.001239975,0.0007756682,0.001218507,0.001736113,0.0005715817,0.05373597],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01962334,"threshold_uncertainty_score":0.06564659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08989797324482983,"score_gpt":0.2982459555053211,"score_spread":0.2083479822604912,"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."}}