{"id":"W1977507713","doi":"10.1007/s10878-007-9106-0","title":"Lower bounds and a tabu search algorithm for the minimum deficiency problem","year":2007,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Advanced Graph Theory Research","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"","keywords":"Combinatorics; Mathematics; Vertex (graph theory); Theory of computation; Tabu search; Graph; Graph coloring; Edge coloring; Neighbourhood (mathematics); Discrete mathematics; Algorithm; Graph power; Line graph","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":[0.00280191,0.001573508,0.001659615,0.002642847,0.001291467,0.003546089,0.002794055,0.002572587,0.01383881],"category_scores_gemma":[0.02103256,0.0009458388,0.001080679,0.002969294,0.001578911,0.003285679,0.001916695,0.003418273,0.002012081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002161776,"about_ca_system_score_gemma":0.002251155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003618048,"about_ca_topic_score_gemma":0.004260957,"domain_scores_codex":[0.9982721,0.0006973692,0.00007089401,0.0001910791,0.0005416803,0.0002268941],"domain_scores_gemma":[0.9915793,0.006286535,0.0003297918,0.0007306535,0.0008668545,0.0002068878],"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":[0.001155396,0.0005334638,0.001419672,0.0003727566,0.00008670417,0.00008565343,0.0002307112,0.6272544,0.003268048,0.112613,0.01994006,0.2330402],"study_design_scores_gemma":[0.0001315475,0.0000866929,0.0002147039,0.00005673176,0.00002137047,0.00004476806,0.0000383572,0.9256779,0.0006932708,0.07069474,0.00232228,0.00001763579],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06201036,0.001810464,0.9033445,0.002158985,0.0004226876,0.0002712964,0.0007265962,0.001668011,0.02758714],"genre_scores_gemma":[0.252735,0.0006799999,0.7356752,0.0005315056,0.0002470422,0.0005371479,0.001413698,0.0007328331,0.007447602],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01383881,"threshold_uncertainty_score":0.0462954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01375133543579926,"score_gpt":0.2907933059047155,"score_spread":0.2770419704689163,"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."}}