{"id":"W2128634904","doi":"10.1145/2629656","title":"Gathering Despite Mischief","year":2014,"lang":"en","type":"article","venue":"ACM Transactions on Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Outaouais","funders":"Israeli Centers for Research Excellence; Natural Sciences and Engineering Research Council of Canada; Israel Science Foundation; United States-Israel Binational Science Foundation","keywords":"Byzantine architecture; Computer science; Node (physics); Upper and lower bounds; Matching (statistics); Combinatorics; Theoretical computer science; Mathematics; Discrete mathematics; Physics; Geography","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":[0.003038284,0.001337432,0.001325645,0.0006414455,0.003311247,0.002142109,0.003119156,0.00217349,0.006486794],"category_scores_gemma":[0.02033135,0.0009184172,0.001035526,0.0009222307,0.002427721,0.005222627,0.005177342,0.002285892,0.001730348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001449037,"about_ca_system_score_gemma":0.001790999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002734772,"about_ca_topic_score_gemma":0.003851533,"domain_scores_codex":[0.996595,0.0008708664,0.0001978672,0.001189252,0.0005262076,0.0006207973],"domain_scores_gemma":[0.9825736,0.006835528,0.001703426,0.00660445,0.001413599,0.0008694233],"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":[0.002006485,0.0003331543,0.0130625,0.001577049,0.0003678363,0.002061824,0.006292228,0.2880429,0.04537805,0.3169556,0.02693666,0.2969857],"study_design_scores_gemma":[0.0001798655,0.0005942662,0.00267772,0.0001870698,0.0001890683,0.001401202,0.001292863,0.6580473,0.02416782,0.2505366,0.06064176,0.00008455909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1466503,0.0005145654,0.8225099,0.003457667,0.0001529378,0.0003009569,0.0004568974,0.00238247,0.02357423],"genre_scores_gemma":[0.7280418,0.0003453796,0.2542703,0.0006365247,0.0001029608,0.000321493,0.0006896717,0.0004508366,0.01514111],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006486794,"threshold_uncertainty_score":0.0217005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02024123927452412,"score_gpt":0.2543549482875596,"score_spread":0.2341137090130355,"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."}}