{"id":"W2510377198","doi":"","title":"GPSPA: a new adaptive algorithm for maintaining shortest path routing trees in stochastic networks: Research Articles","year":2004,"lang":"en","type":"article","venue":"International Journal of Communication Systems","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Shortest path problem; Computer science; Constrained Shortest Path First; K shortest path routing; Private Network-to-Network Interface; Shortest Path Faster Algorithm; Yen's algorithm; Algorithm; Path (computing); Mathematical optimization; Average path length; Routing (electronic design automation); Convergence (economics); Link-state routing protocol; Dijkstra's algorithm; Routing protocol; Mathematics; Theoretical computer science; Computer network; Graph","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":[0.0008821078,0.000759549,0.0009256031,0.0007310992,0.0004833835,0.0009894571,0.001428857,0.001336708,0.001600679],"category_scores_gemma":[0.002596311,0.0003751874,0.0006015151,0.001233663,0.0008478271,0.001739845,0.001400167,0.001537261,0.0007099244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005743998,"about_ca_system_score_gemma":0.001108706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002973733,"about_ca_topic_score_gemma":0.002122902,"domain_scores_codex":[0.9994658,0.0001294577,0.00003164628,0.0001151547,0.0002113255,0.00004661903],"domain_scores_gemma":[0.9994298,0.0002772539,0.00006117821,0.00006875093,0.0001237235,0.00003939031],"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":[0.0001193464,0.00005875081,0.000540072,0.0001545491,0.00008185645,0.00007511391,0.0001036113,0.5706481,0.007117783,0.03404572,0.005647789,0.3814073],"study_design_scores_gemma":[0.00001666454,0.00004099138,0.00007489448,0.000007567761,0.000007650259,0.00004238841,0.000008017105,0.985611,0.0008440605,0.00918368,0.004154098,0.000008949981],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003480625,0.0003862823,0.9949489,0.0001255267,0.00006309242,0.00002546234,0.00002304534,0.0002685705,0.0006785647],"genre_scores_gemma":[0.135076,0.001284634,0.8587724,0.0002260256,0.0002105191,0.0001963098,0.0002711852,0.0001739516,0.003789046],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002973733,"threshold_uncertainty_score":0.00591284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06935098984981178,"score_gpt":0.3724407295829069,"score_spread":0.3030897397330951,"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."}}