{"id":"W2145384761","doi":"10.1109/icnp.1993.340898","title":"On token protocols for high-speed multiple-ring networks","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Token ring; Token bus network; Computer network; Security token; Token passing; Computer science; Throughput; Fiber Distributed Data Interface; Ring (chemistry); Gigabit; Transmission (telecommunications); Protocol (science); Channel (broadcasting); Ring network; Local area network; Network topology; Telecommunications; Wireless","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":[0.002828555,0.001419157,0.0008258518,0.001655002,0.001578371,0.003557987,0.002056999,0.002066689,0.007853786],"category_scores_gemma":[0.005047164,0.000891024,0.000889609,0.003122888,0.003602215,0.009369414,0.002828272,0.004928811,0.003156035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002526043,"about_ca_system_score_gemma":0.001495054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001676258,"about_ca_topic_score_gemma":0.001454397,"domain_scores_codex":[0.9975914,0.000787036,0.0001726526,0.0002399734,0.0009622499,0.0002467564],"domain_scores_gemma":[0.9982376,0.0009680371,0.0001040508,0.0003113793,0.0002882909,0.00009063814],"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":[0.00007516499,0.00002639702,0.00007246326,0.0001451522,0.00001759546,0.0001914363,0.000251374,0.008244944,0.001435286,0.9414613,0.01017353,0.03790525],"study_design_scores_gemma":[0.00006129411,0.00006216436,0.00007979026,0.0001791293,0.00002428541,0.0002577185,0.00006676243,0.04196977,0.002073243,0.7679784,0.1871961,0.00005134774],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003737515,0.01267063,0.8999135,0.002643104,0.001968421,0.000370708,0.0001987172,0.0009979355,0.07749949],"genre_scores_gemma":[0.2721566,0.04745346,0.5674109,0.004562541,0.005260058,0.002564083,0.0009988811,0.001061806,0.09853182],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007853786,"threshold_uncertainty_score":0.02627349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02467286708503926,"score_gpt":0.246027219837499,"score_spread":0.2213543527524598,"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."}}