{"id":"W2075234757","doi":"10.1016/j.endm.2013.05.097","title":"Stronger Lower Bounds for the Quadratic Minimum Spanning Tree Problem with Adjacency Costs","year":2013,"lang":"en","type":"article","venue":"Electronic Notes in Discrete Mathematics","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"Fundação de Amparo à Pesquisa do Estado de Minas Gerais; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Spanning tree; Mathematics; Minimum spanning tree; Adjacency list; Quadratic equation; Combinatorics; Minimum degree spanning tree; Column generation; Tree (set theory); Mathematical optimization; Linear programming; Upper and lower bounds; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001528899,0.0002385819,0.0002228515,0.00005747984,0.00009794215,0.00009695294,0.0002130777,0.00006921849,0.0000390176],"category_scores_gemma":[0.0001008451,0.0001588577,0.00004557702,0.0001353458,0.00006452164,0.0001675061,0.00002316942,0.0002587985,0.00001260302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002231994,"about_ca_system_score_gemma":0.00003785324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001240982,"about_ca_topic_score_gemma":0.0001406043,"domain_scores_codex":[0.998771,0.00001100308,0.0002987673,0.0001764658,0.0001537751,0.0005890161],"domain_scores_gemma":[0.9989604,0.0005480939,0.00007508832,0.0003332461,0.00004313532,0.00004000129],"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":[0.00002064752,0.00007313646,0.00006068144,0.0003402129,0.0001049777,0.000001281792,0.001040572,0.9756598,0.000333433,0.01535814,0.000255387,0.006751771],"study_design_scores_gemma":[0.0007450125,0.000302061,0.00009826141,0.0002126059,0.00007372168,0.000007130001,0.0003284202,0.9514019,0.00217325,0.04387654,0.000336711,0.000444401],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01986941,0.000537555,0.9768585,0.0001736528,0.00007142661,0.001058014,0.000003885273,0.0001643433,0.00126319],"genre_scores_gemma":[0.9141214,0.00006564805,0.08500567,0.00001552896,0.00005246847,0.0004193099,0.0000142793,0.00007266874,0.0002330642],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8942519,"threshold_uncertainty_score":0.6478029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007557376348709966,"score_gpt":0.2212602827102928,"score_spread":0.2137029063615828,"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."}}