{"id":"W2035762900","doi":"10.1145/1595391.1595392","title":"Improved Separations between Nondeterministic and Randomized Multiparty Communication","year":2009,"lang":"en","type":"article","venue":"ACM Transactions on Computation Theory","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Division of Computing and Communication Foundations","keywords":"Mathematics; Nondeterministic algorithm; Constant (computer programming); Combinatorics; Function (biology); Communication complexity; Binary logarithm; Discrete mathematics; Set (abstract data type); Computer science","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":[0.005525179,0.001090457,0.001622649,0.001007451,0.0016564,0.003616252,0.003767629,0.002762533,0.008154783],"category_scores_gemma":[0.02115308,0.001099266,0.001763693,0.001172179,0.003772979,0.01249495,0.007998616,0.01092823,0.002403887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002827545,"about_ca_system_score_gemma":0.002287949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005593744,"about_ca_topic_score_gemma":0.0005436743,"domain_scores_codex":[0.9922991,0.002662572,0.0003569305,0.001632013,0.002022894,0.001026526],"domain_scores_gemma":[0.9773187,0.01338041,0.0009712725,0.006775375,0.0007785286,0.0007757652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0008799177,0.000173126,0.0003619391,0.0002188877,0.00003642899,0.0001629854,0.0003523947,0.0447836,0.007433796,0.9138314,0.002364812,0.02940087],"study_design_scores_gemma":[0.0001592074,0.0001398428,0.0002027064,0.00006199245,0.00003921907,0.0001724713,0.00005713225,0.2335299,0.01412635,0.7419555,0.009489058,0.00006656391],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0647071,0.001038984,0.897926,0.00233535,0.0002630903,0.0001459737,0.0002992721,0.002026107,0.03125805],"genre_scores_gemma":[0.7649598,0.0005201204,0.2205563,0.0006347934,0.0001906223,0.0004026768,0.0003250739,0.0004905273,0.01192024],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008154783,"threshold_uncertainty_score":0.02922022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02359461181519825,"score_gpt":0.2962639757253391,"score_spread":0.2726693639101408,"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."}}