{"id":"W2352853179","doi":"","title":"The genetic algorithms to solve MDR problem","year":2001,"lang":"en","type":"article","venue":"","topic":"Mobile Agent-Based Network Management","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"CAE (Canada)","funders":"","keywords":"Computer science; Genetic algorithm; Routing (electronic design automation); Service (business); Mathematical optimization; Algorithm; Computer network; Mathematics; Machine learning","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":[0.0007010371,0.0006514743,0.0006256877,0.0007480907,0.0005391458,0.0007137702,0.0006197016,0.001107937,0.001748397],"category_scores_gemma":[0.00232751,0.000288088,0.0005772103,0.001058716,0.0006550508,0.0007293288,0.0006033013,0.001531882,0.0002992723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005803356,"about_ca_system_score_gemma":0.001264379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005842527,"about_ca_topic_score_gemma":0.003352569,"domain_scores_codex":[0.9996139,0.0001574298,0.00001896567,0.00005257692,0.000116978,0.00004013058],"domain_scores_gemma":[0.9995853,0.0002492619,0.00003599625,0.00002605652,0.00008906049,0.0000144162],"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":[0.00002703397,0.00004575514,0.0004895721,0.00009593656,0.00007641643,0.00007070114,0.00008129391,0.8174273,0.0008631973,0.0808188,0.00358123,0.0964227],"study_design_scores_gemma":[0.00003414658,0.00002820019,0.0001477398,0.00002288819,0.00002284045,0.00005126874,0.00002259669,0.9487289,0.0004384893,0.04478639,0.005705386,0.0000111291],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009135034,0.0015593,0.9796673,0.0005282295,0.0001318826,0.00005159273,0.00003240733,0.0001839498,0.008710287],"genre_scores_gemma":[0.3121283,0.004139157,0.6714993,0.000529119,0.000247584,0.0004366804,0.0002386537,0.0001093578,0.01067181],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005842527,"threshold_uncertainty_score":0.01161706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01321584479069079,"score_gpt":0.230316020553425,"score_spread":0.2171001757627342,"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."}}