{"id":"W2170154411","doi":"10.1109/soac.1991.143848","title":"An efficient simulated annealing algorithm for graph bisectioning","year":2002,"lang":"en","type":"article","venue":"","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Simulated annealing; Computer science; Algorithm; Adaptive simulated annealing; Graph; Random graph; Theoretical 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":[0.0007686887,0.001124113,0.00147279,0.001056599,0.0008262757,0.001037988,0.001585459,0.001339374,0.004541576],"category_scores_gemma":[0.00236804,0.0007957807,0.001233226,0.001371149,0.0007449943,0.001485799,0.001210293,0.001483944,0.001469006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001061534,"about_ca_system_score_gemma":0.00145546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003808563,"about_ca_topic_score_gemma":0.004514837,"domain_scores_codex":[0.9988888,0.000392487,0.00007115801,0.0002086904,0.0003667551,0.00007203224],"domain_scores_gemma":[0.9991001,0.0003928626,0.00005933069,0.0001768023,0.0002414454,0.0000295939],"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":[0.00009687164,0.0000676079,0.0002802037,0.0001685133,0.0001045909,0.00007238715,0.0001151234,0.7391449,0.00902424,0.03660443,0.004673134,0.2096482],"study_design_scores_gemma":[0.00003185058,0.00003377007,0.00007659714,0.00001048965,0.00001799655,0.00005875551,0.00001158851,0.9756684,0.003217118,0.01062098,0.01023851,0.00001385619],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001590048,0.0001384603,0.9961261,0.00004580092,0.00003031367,0.00005023972,0.00002993458,0.0006594879,0.001329717],"genre_scores_gemma":[0.0504047,0.0002575367,0.9456356,0.00005641425,0.00002653844,0.0003111276,0.0002364813,0.0002242615,0.002847423],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004541576,"threshold_uncertainty_score":0.0151931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02459489648272742,"score_gpt":0.2534859118683615,"score_spread":0.2288910153856341,"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."}}