{"id":"W3124752832","doi":"10.2139/ssrn.423560","title":"Approximate Local Search in Combinatorial Optimization","year":2003,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Combinatorial optimization; Local search (optimization); Tabu search; Mathematics; Mathematical optimization; Combinatorics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016518,0.00009728948,0.0001064415,0.0002052009,0.0001347097,0.0001303121,0.0002581798,0.00007305001,0.000038927],"category_scores_gemma":[0.00005091551,0.00009678963,0.00004238624,0.0004914364,0.00003411574,0.0005101275,0.00002615221,0.001045488,0.00001182583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007463834,"about_ca_system_score_gemma":0.001693374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001393911,"about_ca_topic_score_gemma":0.0000627957,"domain_scores_codex":[0.9979801,0.0002155597,0.0002357647,0.000188638,0.0002612776,0.001118703],"domain_scores_gemma":[0.9996083,0.00003073916,0.00006551622,0.0001444508,0.00008338335,0.0000676304],"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":[0.00000573199,0.00003453909,0.0006223209,0.000001123424,0.000007630491,0.000002549339,0.00009276285,0.210059,0.000007952623,0.7694842,0.000004469583,0.01967773],"study_design_scores_gemma":[0.002103091,0.0001732747,0.0002293761,0.00001231922,0.000004239982,0.0006461661,0.0006414606,0.7918283,0.0001729247,0.2037075,0.0002427649,0.0002385399],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002302493,0.0001274052,0.9946032,0.0003034047,0.0004809315,0.00009499175,1.343947e-7,0.00004234858,0.00204509],"genre_scores_gemma":[0.9825959,0.0004951701,0.01671004,0.00005061478,0.00003866139,0.000002919923,0.000001286401,0.000008473147,0.00009689484],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9802935,"threshold_uncertainty_score":0.4542182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007070504163684968,"score_gpt":0.2277320355363686,"score_spread":0.2206615313726837,"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."}}