{"id":"W4310001488","doi":"10.48550/arxiv.2205.08479","title":"Opportunistic Routing in Quantum Networks","year":2022,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Policy-based routing; Static routing; Link-state routing protocol; Equal-cost multi-path routing; Multipath routing; Routing (electronic design automation); Computer network; Dynamic Source Routing; Path (computing); Distributed computing; Routing protocol","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001341677,0.0003392934,0.0004777709,0.000441047,0.001179168,0.001316019,0.000927871,0.0008809277,0.002883137],"category_scores_gemma":[0.004004998,0.0003330904,0.0003711593,0.000616586,0.001294843,0.002211103,0.001215444,0.0007918322,0.0002086518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002044706,"about_ca_system_score_gemma":0.001644879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003554221,"about_ca_topic_score_gemma":0.004480549,"domain_scores_codex":[0.9990788,0.0003909913,0.00003241505,0.0001195097,0.0002139479,0.0001643892],"domain_scores_gemma":[0.997731,0.001361788,0.0001838731,0.00041527,0.0002090497,0.00009891549],"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":[0.0001376406,0.00005306193,0.0005842407,0.00005853022,0.00002898619,0.00009355609,0.0001060175,0.8001988,0.003253428,0.1793161,0.001892741,0.01427694],"study_design_scores_gemma":[0.00001360644,0.00001856592,0.00008232542,0.000004981397,0.000006934569,0.00001996553,0.0000225112,0.9570779,0.0007686075,0.04038488,0.001591037,0.000008635002],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2460084,0.0007984961,0.7228912,0.001289928,0.0001863849,0.0002094458,0.0002724099,0.001059251,0.02728453],"genre_scores_gemma":[0.9482409,0.000308231,0.04767311,0.0001603261,0.00002322687,0.0001467807,0.00007888303,0.00007015144,0.003298349],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003554221,"threshold_uncertainty_score":0.01483548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05654096027359945,"score_gpt":0.1923878224840833,"score_spread":0.1358468622104839,"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."}}