{"id":"W4256694195","doi":"10.32920/ryerson.14648535.v1","title":"Survivability in ATM networks","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Survivability; Spare part; Network planning and design; Computer science; Computer network; Path (computing); Reliability engineering; Event (particle physics); Service (business); Engineering; Operations management; Business","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":[0.0003673338,0.0003253273,0.0002102102,0.0007349874,0.0004732946,0.001038674,0.0002742167,0.0003997687,0.003613204],"category_scores_gemma":[0.001865991,0.0001453611,0.0002358786,0.0008857428,0.0007172526,0.001176801,0.0006370331,0.0007890178,0.0004299408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007635673,"about_ca_system_score_gemma":0.0002422508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001244459,"about_ca_topic_score_gemma":0.0004358788,"domain_scores_codex":[0.9996105,0.0001149919,0.00001422627,0.00006011844,0.0001571468,0.00004308723],"domain_scores_gemma":[0.9994767,0.0003059643,0.00007256335,0.00003929441,0.00008039502,0.00002505676],"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":[0.0001114347,0.00004663883,0.001097605,0.0002316126,0.00002769963,0.0002703329,0.000319246,0.2116295,0.0114771,0.5676966,0.004731942,0.2023603],"study_design_scores_gemma":[0.00001418717,0.00007899456,0.0009247373,0.00006327617,0.0000123887,0.0003701114,0.0001618256,0.3749459,0.003789565,0.6009007,0.01872302,0.00001533151],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2025045,0.01768535,0.6367218,0.003049203,0.0004245586,0.0001068595,0.0004471183,0.0005644359,0.1384961],"genre_scores_gemma":[0.9637474,0.005044171,0.02188712,0.0001123711,0.0002977726,0.00006864665,0.0001507059,0.00004446416,0.008647299],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003613204,"threshold_uncertainty_score":0.01208735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01267512689003593,"score_gpt":0.229141224048425,"score_spread":0.216466097158389,"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."}}