{"id":"W2130052144","doi":"10.1364/jon.5.000493","title":"Characterization of pre-cross-connected trails for optical mesh network protection","year":2006,"lang":"en","type":"article","venue":"Journal of Optical Networking","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Path protection; Heuristic; Path (computing); Connection (principal bundle); Computer science; Engineering; Computer network; Distributed computing; Topology (electrical circuits); Artificial intelligence; Structural engineering; Electrical engineering; Wavelength-division multiplexing","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":[],"consensus_categories":[],"category_scores_codex":[0.0004724798,0.0002496524,0.0005671202,0.0001149563,0.0000853585,0.00006750842,0.0002573688,0.0003273702,0.00000807981],"category_scores_gemma":[0.0001656222,0.0002293111,0.0002245525,0.0004986902,0.0001697611,0.0003544381,0.00004070566,0.0005281942,9.258291e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001054412,"about_ca_system_score_gemma":0.00002111273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.505363e-7,"about_ca_topic_score_gemma":0.000001947007,"domain_scores_codex":[0.997745,0.00001484892,0.001170556,0.0001799713,0.0003059978,0.000583618],"domain_scores_gemma":[0.9987786,0.0003312687,0.0003321541,0.0001834474,0.0002813569,0.00009314557],"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":[0.0003781989,0.000104694,0.0005673643,0.0001250705,0.0001142579,0.000009153382,0.00001540034,0.761902,0.1952211,0.01269596,0.0001080282,0.02875886],"study_design_scores_gemma":[0.003020088,0.001273904,0.04098776,0.001062078,0.0002685835,0.0002673265,0.00001970291,0.874691,0.05302113,0.01737775,0.007087671,0.0009229744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.453327,0.0001579844,0.5450121,0.00005936415,0.0007312721,0.0003239346,0.000002493577,0.0001519143,0.0002339953],"genre_scores_gemma":[0.87511,0.00007363757,0.1219697,0.0000109546,0.002723588,0.00002589708,0.000009718963,0.00005960502,0.00001695828],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4230424,"threshold_uncertainty_score":0.9351035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0134267903063458,"score_gpt":0.241435003253726,"score_spread":0.2280082129473802,"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."}}