{"id":"W4379140848","doi":"10.1016/j.asoc.2023.110486","title":"A multi-objective genetic algorithm for compression of weighted graphs to simplify epidemic analysis","year":2023,"lang":"en","type":"article","venue":"Applied Soft Computing","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Thompson Rivers University; Brock University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Compression (physics); Distortion (music); Algorithm; Data compression; Mathematical optimization; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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"],"consensus_categories":[],"category_scores_codex":[0.0003886682,0.0002428906,0.000696243,0.0006190517,0.0002312446,0.00002679488,0.0003280062,0.00005486115,0.00002431937],"category_scores_gemma":[0.000007188176,0.0002457357,0.0004401916,0.002980937,0.00004054192,0.000020374,0.0002921752,0.0001417677,0.00001399904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002651879,"about_ca_system_score_gemma":0.00002228982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001916587,"about_ca_topic_score_gemma":0.000006351518,"domain_scores_codex":[0.9981669,0.00005417687,0.000594352,0.0005451489,0.0001916814,0.0004477721],"domain_scores_gemma":[0.9983369,0.0006846299,0.0003175482,0.0004034499,0.0001457769,0.0001117316],"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":[0.00002783746,0.0002171406,0.03707518,0.00003117346,0.00274989,9.912457e-7,0.001175282,0.09935556,0.01096707,0.002808733,0.001801213,0.8437899],"study_design_scores_gemma":[0.0004105814,0.00002859034,0.02027441,0.00002576213,0.000478637,8.012436e-8,0.0002344611,0.9663095,0.002798925,0.008985003,0.0001840177,0.0002699602],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1781191,0.00001660483,0.8208178,0.00001445613,0.00002853808,0.0005916734,0.00003633083,0.0002364042,0.0001391151],"genre_scores_gemma":[0.6892086,6.509656e-7,0.3104284,0.00003244727,0.00008751957,0.00007483485,0.0001287643,0.00002497051,0.00001377968],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.866954,"threshold_uncertainty_score":0.9999995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01722078671374833,"score_gpt":0.3031368497632969,"score_spread":0.2859160630495485,"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."}}