{"id":"W2064449485","doi":"10.1007/978-3-642-13495-1_50","title":"Biogeography Migration Algorithm for Traveling Salesman Problem","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Department of National Defence","funders":"","keywords":"Travelling salesman problem; Computer science; Algorithm; Mathematical optimization; Optimization problem; Operator (biology); Optimization algorithm; 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":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001827672,0.0005624992,0.000554655,0.00152856,0.0004768046,0.001061702,0.00359525,0.0005158284,0.00002830946],"category_scores_gemma":[0.0001473252,0.0005277743,0.000230719,0.001131786,0.0007444781,0.0006043694,0.0007299192,0.001087958,0.00002891352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001337419,"about_ca_system_score_gemma":0.0007248776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000241351,"about_ca_topic_score_gemma":0.00009796575,"domain_scores_codex":[0.9951067,0.00004255553,0.000730287,0.001879027,0.001385105,0.0008563185],"domain_scores_gemma":[0.9963921,0.0006717208,0.0003567338,0.001406936,0.000893238,0.0002793264],"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":[0.000002062341,0.00003033466,0.0000119849,0.00003643427,0.00001329433,0.00001426526,0.0002536984,0.006194521,0.000208558,0.007876351,0.00001311875,0.9853454],"study_design_scores_gemma":[0.0003021779,0.0001538438,0.00001851933,0.0001189852,0.000008419641,0.00003187568,7.510515e-8,0.873276,0.001954542,0.119733,0.0038708,0.000531817],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000004148241,0.0001878543,0.9949199,0.0008739101,0.001631571,0.001261227,0.0000294741,0.000201717,0.0008902196],"genre_scores_gemma":[0.0003902107,0.00007572239,0.9980191,0.0004310728,0.0005683475,0.00005976504,0.00003844651,0.00004944115,0.0003678775],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9848136,"threshold_uncertainty_score":0.9999753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0191236674805783,"score_gpt":0.2678947300122788,"score_spread":0.2487710625317004,"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."}}