{"id":"W89723526","doi":"","title":"The AntSynNet Algorithm: Network Syntheses Using Ant Colony Optimization.","year":2004,"lang":"en","type":"article","venue":"International Conference on Artificial Intelligence","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Ant colony optimization algorithms; Computer science; Heuristics; Metaheuristic; Routing (electronic design automation); Heuristic; Mathematical optimization; Domain (mathematical analysis); Ant colony; Process (computing); Set (abstract data type); Parallel metaheuristic; Algorithm; Artificial intelligence; Meta-optimization; Mathematics; Computer network","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005772587,0.0008602885,0.0007156671,0.0008638802,0.0005759153,0.0009510299,0.001260644,0.0009299678,0.004620687],"category_scores_gemma":[0.001360775,0.0004600026,0.000517725,0.0008522008,0.0006748787,0.001050895,0.0009072799,0.0009375666,0.00152459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006118398,"about_ca_system_score_gemma":0.001483561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002073116,"about_ca_topic_score_gemma":0.003642079,"domain_scores_codex":[0.9997241,0.00005822657,0.00001434873,0.00005292608,0.0001286798,0.00002167075],"domain_scores_gemma":[0.9996625,0.0001427086,0.00006090531,0.00004380123,0.00006824142,0.00002179439],"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":[0.0001051671,0.0001029134,0.0006203908,0.0003753116,0.0001093478,0.000179075,0.0001263912,0.6281785,0.01199868,0.05254047,0.01530342,0.2903603],"study_design_scores_gemma":[0.00004910025,0.00005443679,0.0001291689,0.00004371562,0.00002498407,0.0001670527,0.00003478122,0.9370515,0.005775434,0.01591792,0.04073152,0.00002039626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00661247,0.001104891,0.9710087,0.0002361958,0.0002530426,0.0002292725,0.0001934408,0.002318554,0.01804348],"genre_scores_gemma":[0.05667185,0.0008750662,0.9310694,0.0001443353,0.00005307724,0.0005000443,0.0004570418,0.0005322929,0.009696942],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004620687,"threshold_uncertainty_score":0.01545781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07995878778245127,"score_gpt":0.3109012267291485,"score_spread":0.2309424389466973,"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."}}