{"id":"W2130150993","doi":"10.1109/tpds.2006.34","title":"Efficient algorithms for minimum congestion hypergraph embedding in a cycle","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Parallel and Distributed Systems","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Hypergraph; Embedding; Computer science; Algorithm; Node (physics); Computational complexity theory; Approximation algorithm; Set (abstract data type); Enhanced Data Rates for GSM Evolution; Time complexity; Mathematics; Discrete mathematics","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":[0.000676701,0.00118024,0.001052185,0.001488411,0.0008025886,0.001545376,0.0016437,0.001200134,0.00611794],"category_scores_gemma":[0.004176782,0.0007107774,0.0007363721,0.002265791,0.0006260271,0.003553208,0.002346617,0.001260489,0.001271905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001423794,"about_ca_system_score_gemma":0.001750873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003350584,"about_ca_topic_score_gemma":0.004502552,"domain_scores_codex":[0.999069,0.0002445916,0.00006533335,0.0002043476,0.0002427259,0.0001738952],"domain_scores_gemma":[0.998446,0.000642052,0.0001783734,0.0003720344,0.0002645375,0.00009690253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004621517,0.0002954004,0.001140362,0.0004598947,0.00008528718,0.0001667185,0.0004009689,0.3807276,0.01013762,0.07629316,0.01992097,0.5099098],"study_design_scores_gemma":[0.0001144187,0.0000718335,0.000230821,0.00002854822,0.00002211704,0.0001202644,0.0001224614,0.9111037,0.003837126,0.07792909,0.006397686,0.00002198496],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04194253,0.0007260432,0.9468988,0.0004395966,0.0000752229,0.0002897557,0.0003468556,0.002929031,0.006352044],"genre_scores_gemma":[0.1970959,0.0004625312,0.7963168,0.00009444489,0.00004151711,0.000367786,0.001248043,0.0003527956,0.004020242],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00611794,"threshold_uncertainty_score":0.02046657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01537991793278134,"score_gpt":0.2475555644455234,"score_spread":0.232175646512742,"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."}}