{"id":"W136384337","doi":"","title":"A Kohonen-like decomposition method for the traveling salesman problem—KNIES_DECOMPOSE","year":2000,"lang":"en","type":"article","venue":"European Conference on Artificial Intelligence","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Travelling salesman problem; Euclidean geometry; Partition (number theory); 2-opt; Heuristic; Self-organizing map; Computer science; Mathematical optimization; Bottleneck traveling salesman problem; Decomposition; Artificial neural network; Traveling purchaser problem; Euclidean distance; Mathematics; Algorithm; Artificial intelligence; Combinatorics","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002366659,0.0002995902,0.0002553279,0.0001327035,0.0006699442,0.0009900723,0.002196315,0.00005165828,0.001221052],"category_scores_gemma":[0.0001579686,0.0002356665,0.0001462993,0.0006275065,0.0001603972,0.0003052105,0.0001729452,0.0003816768,0.002315703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005031876,"about_ca_system_score_gemma":0.0001155999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002427169,"about_ca_topic_score_gemma":0.00001566119,"domain_scores_codex":[0.9964073,0.0008543801,0.0007430866,0.0008402077,0.0005727174,0.0005823247],"domain_scores_gemma":[0.9972516,0.001043839,0.0001573018,0.0009925598,0.0003531922,0.0002014989],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006045899,0.0001180741,5.131996e-7,0.000009397104,0.0000218679,0.00001408785,0.0007009565,0.0233527,0.0005791508,0.1205236,0.0002678655,0.8543513],"study_design_scores_gemma":[0.00007221663,0.0002555154,0.00003819004,0.00005479262,0.00001281147,0.00002028122,0.0000851205,0.9699511,0.003627955,0.01404556,0.01153801,0.0002984543],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001364752,0.0000587596,0.9754575,0.003392072,0.0003818856,0.0008990545,0.00001282874,0.0002318016,0.01942961],"genre_scores_gemma":[0.175468,0.0003589658,0.8184929,0.001401717,0.0003477509,0.0001212099,0.00002271423,0.00006832259,0.003718388],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9465984,"threshold_uncertainty_score":0.999692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1107698732265577,"score_gpt":0.3762386932067224,"score_spread":0.2654688199801648,"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."}}