{"id":"W2266731991","doi":"10.1016/j.tcs.2016.01.037","title":"Topology recognition and leader election in colored networks","year":2016,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Narodowe Centrum Nauki","keywords":"Node (physics); Colored; Leader election; Computer science; Topology (electrical circuits); Upper and lower bounds; Network topology; Path (computing); Theoretical computer science; Mathematics; Computer network; Combinatorics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001465597,0.0003786767,0.0007349601,0.0007415889,0.001057173,0.002046101,0.001582491,0.001119763,0.002015925],"category_scores_gemma":[0.009479694,0.0004880971,0.0004307104,0.0008789122,0.001616991,0.002286204,0.001418337,0.001104028,0.0003544401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001223153,"about_ca_system_score_gemma":0.001121482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00383724,"about_ca_topic_score_gemma":0.003721228,"domain_scores_codex":[0.9988674,0.00044756,0.00003844122,0.0002151816,0.0001946714,0.0002366914],"domain_scores_gemma":[0.9948137,0.003237204,0.0005704502,0.000544875,0.0004521646,0.0003816224],"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":[0.0004363003,0.0001076982,0.001643909,0.0001056075,0.00004246411,0.0002212332,0.0003639442,0.5556809,0.008643077,0.3836798,0.002968374,0.04610668],"study_design_scores_gemma":[0.00002217817,0.00002411317,0.0001991503,0.000004754971,0.000008079921,0.00003069462,0.00004615549,0.8815054,0.001540048,0.115923,0.0006845507,0.00001197216],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1399082,0.0003786873,0.8494956,0.0007347902,0.0002330268,0.00006084651,0.00006396716,0.00049823,0.008626638],"genre_scores_gemma":[0.9375241,0.0002728781,0.05478176,0.0001199967,0.00007105448,0.0000574317,0.00009014756,0.00008450895,0.006998061],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00383724,"threshold_uncertainty_score":0.008874595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0137087119819757,"score_gpt":0.2369135803316581,"score_spread":0.2232048683496824,"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."}}