{"id":"W1963660119","doi":"10.1145/2641483.2641531","title":"Exploring the diameter and broadcast time of general Knödel graphs using extensive simulations","year":2008,"lang":"en","type":"article","venue":"","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Graph; Upper and lower bounds; Gossip; Broadcasting (networking); Dissemination; Theoretical computer science; Binary logarithm; Complete graph; Combinatorics; Computer network; Mathematics; Telecommunications","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":[0.00008245594,0.00006404914,0.0001016645,0.00006184466,0.0001876518,0.0000340702,0.0001365277,0.00001522687,0.00001159421],"category_scores_gemma":[0.00001056659,0.00004151117,0.00004481614,0.0001903959,0.00005058104,0.000369931,0.00005995312,0.00004457658,0.000003948888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007147246,"about_ca_system_score_gemma":0.00001053992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001532003,"about_ca_topic_score_gemma":0.000004942232,"domain_scores_codex":[0.9994305,0.00004888141,0.000166331,0.000143812,0.0001002869,0.0001101552],"domain_scores_gemma":[0.9994878,0.0001048533,0.00005017412,0.0002226931,0.0001062689,0.00002825434],"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":[0.00003387707,0.0002208187,0.01280139,0.00004820901,0.0003892728,0.00007278649,0.04828854,0.5613855,0.1502413,0.1767364,0.007003469,0.04277846],"study_design_scores_gemma":[0.00009626313,0.00002431424,0.002355626,0.0000114206,0.000003198205,0.00009153448,0.00005425392,0.9953296,0.001473447,0.000265577,0.0002208885,0.0000738387],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6989836,0.00003989545,0.3002494,0.000057148,0.0002116602,0.00006293046,6.309613e-7,0.00002263697,0.0003721825],"genre_scores_gemma":[0.9914677,0.00001367822,0.007849802,0.000139614,0.00007155769,0.000002741951,2.453181e-7,0.000004131037,0.0004505649],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4339441,"threshold_uncertainty_score":0.1692776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1161670550561656,"score_gpt":0.2543017114525012,"score_spread":0.1381346563963357,"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."}}