{"id":"W2101381179","doi":"10.1109/glocom.1997.644577","title":"A flexible virtual path topology design algorithm","year":2002,"lang":"en","type":"article","venue":"","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Network topology; Overlay; Overlay network; Distributed computing; Computer network; Bandwidth (computing); Path (computing); Routing (electronic design automation); Topology (electrical circuits); Logical topology; Algorithm design; Algorithm; Engineering; The Internet","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001483095,0.00009699851,0.0001161992,0.00004598413,0.00009080953,0.00007161061,0.0004842517,0.00005793706,0.000679522],"category_scores_gemma":[0.000009754139,0.00008183197,0.00004116449,0.0002061112,0.00003782326,0.0001947582,0.00007205548,0.00008749798,0.0008109891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001434974,"about_ca_system_score_gemma":0.00001745077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005360715,"about_ca_topic_score_gemma":6.510132e-7,"domain_scores_codex":[0.9991054,0.00008288813,0.0001338404,0.0002724431,0.0001330393,0.0002723946],"domain_scores_gemma":[0.9993976,0.000128921,0.00002859983,0.000313663,0.00003761104,0.00009359988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[9.11067e-7,0.00003259044,0.000003248025,1.988344e-7,0.0000064961,0.00001334823,0.00007618365,0.0004117464,0.00001018771,0.1289289,0.0207202,0.849796],"study_design_scores_gemma":[0.0003545215,0.0001911155,0.00002008849,0.000001992032,0.000002728614,0.00003094237,0.0000123992,0.9812047,0.00009820574,0.001608536,0.01635266,0.0001220699],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00004517809,0.0002189138,0.9859452,0.002177742,0.000443215,0.00009647336,2.990185e-7,0.0004715369,0.01060144],"genre_scores_gemma":[0.4374393,0.00007523457,0.5114763,0.004387684,0.0003486175,0.00004448173,6.004693e-7,0.00001136197,0.04621645],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.980793,"threshold_uncertainty_score":0.999967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02487142165488833,"score_gpt":0.2159942959800753,"score_spread":0.191122874325187,"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."}}