{"id":"W2312191997","doi":"10.3138/infor.53.1.40","title":"A Hierarchy of Subgraph Projection-Based Semidefinite Relaxations for Some NP-Hard Graph Optimization Problems","year":2015,"lang":"en","type":"article","venue":"INFOR Information Systems and Operational Research","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Group for Research in Decision Analysis; Polytechnique Montréal","funders":"","keywords":"Semidefinite programming; Mathematics; Relaxation (psychology); Hierarchy; Combinatorics; Benchmark (surveying); Projection (relational algebra); Maximum cut; Graph; Mathematical optimization; Discrete mathematics; Algorithm","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.002806281,0.0001326459,0.0001935879,0.00121445,0.0005257609,0.000761803,0.0003859748,0.00009334859,0.000003341564],"category_scores_gemma":[0.0006431554,0.0001188075,0.00007159363,0.001316309,0.0001648196,0.004329397,0.0001041049,0.0001936048,0.000009767183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000760226,"about_ca_system_score_gemma":0.0007864485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002853565,"about_ca_topic_score_gemma":0.000009777954,"domain_scores_codex":[0.9974944,0.0001313464,0.0007772814,0.000188416,0.001119255,0.0002892896],"domain_scores_gemma":[0.9959134,0.0004706073,0.0002240008,0.0003056088,0.002920459,0.0001659197],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003614263,0.00004095161,0.000502392,0.0002281708,0.00002393276,1.514101e-7,0.001655251,0.2593628,0.00001494594,0.733175,0.002945688,0.002014484],"study_design_scores_gemma":[0.001085617,0.0003247775,0.0001851363,0.00008264717,0.00000312241,0.00001328318,0.0003707825,0.9621935,0.0001089416,0.0065797,0.02889288,0.0001595852],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002608398,0.0001680517,0.9920095,0.0008997803,0.000372708,0.001879124,0.0001365565,0.00008926378,0.001836593],"genre_scores_gemma":[0.7387978,0.0001741671,0.2540547,0.0007786367,0.0003599125,0.003761895,0.001345223,0.00003154553,0.0006960321],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7379548,"threshold_uncertainty_score":0.7346084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1272666023801181,"score_gpt":0.3362466144016522,"score_spread":0.2089800120215341,"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."}}