{"id":"W2982460817","doi":"10.48550/arxiv.1910.14289","title":"Expected Complexity of Routing in $Θ$ 6 and Half-$Θ$ 6 Graphs","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Equal-cost multi-path routing; Static routing; Multipath routing; Destination-Sequenced Distance Vector routing; Link-state routing protocol; Combinatorics; Computer science; Mathematics; Dynamic Source Routing; Discrete mathematics; Algorithm; Routing (electronic design automation); Computer network; Routing protocol","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":[0.0002019782,0.0001492212,0.0002502185,0.0003898613,0.0000470012,0.00003999763,0.0005149618,0.0001225594,0.000006696663],"category_scores_gemma":[0.00002643939,0.0001843489,0.0000722699,0.0006903622,0.00008609254,0.0002119647,0.0009523642,0.0002411876,0.000004920418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005637669,"about_ca_system_score_gemma":0.0001102679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002474082,"about_ca_topic_score_gemma":0.00009294749,"domain_scores_codex":[0.9988791,0.0001127741,0.0001894631,0.0005924219,0.00007272419,0.0001535577],"domain_scores_gemma":[0.9991043,0.00009768949,0.0002006935,0.0004271019,0.0001165968,0.00005360661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001493908,0.00006538553,0.01548891,0.00006952056,0.0000255671,0.0000258638,0.0004655652,0.2120211,0.000150423,0.7711281,0.00001872387,0.0005259817],"study_design_scores_gemma":[0.0004414815,0.0000308788,0.05364295,0.00007490613,0.000008627432,0.000002552802,0.00006281966,0.8012636,0.0002129493,0.1440304,0.00001711785,0.0002117555],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.683966,0.00004298762,0.3149506,0.00004128215,0.0001990531,0.0001428905,0.00000377189,0.00003775653,0.0006156465],"genre_scores_gemma":[0.996667,0.00003729797,0.003097835,0.00002290461,0.00001469485,2.961041e-7,0.00001794883,0.000004606687,0.0001373625],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6270977,"threshold_uncertainty_score":0.7517529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.103561986002293,"score_gpt":0.1993505511072041,"score_spread":0.09578856510491114,"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."}}