{"id":"W309977538","doi":"10.1007/978-3-319-16549-3_14","title":"An Experimental Evaluation of Multi-objective Evolutionary Algorithms for Detecting Critical Nodes in Complex Networks","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"Brock University","funders":"","keywords":"Computer science; Evolutionary algorithm; Pairwise comparison; Benchmark (surveying); Algorithm; Complex network; Task (project management); Node (physics); Graph; Theoretical computer science; Artificial intelligence","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"],"consensus_categories":[],"category_scores_codex":[0.001566114,0.0003152007,0.0004900832,0.0004335858,0.000140485,0.00006817642,0.0005642538,0.0001346371,0.00006369757],"category_scores_gemma":[0.00004924829,0.00032519,0.0001327615,0.0002911226,0.0005133075,0.0002359036,0.0002354857,0.0003743588,6.090806e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004649536,"about_ca_system_score_gemma":0.0003009828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000147893,"about_ca_topic_score_gemma":0.00008184921,"domain_scores_codex":[0.9975703,0.00009909039,0.0004911378,0.0007815321,0.0006794293,0.0003785511],"domain_scores_gemma":[0.9980491,0.000437551,0.0002128725,0.000435892,0.0007774462,0.00008713844],"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":[0.00002296705,0.0002016466,0.0009889437,0.000009125216,0.00002260697,0.000001060066,0.0005469068,0.6104461,0.0005361372,0.003222018,0.00001120081,0.3839913],"study_design_scores_gemma":[0.0004007268,0.000151518,0.0004487601,0.0001222191,0.00003088035,0.000001450246,0.000006049329,0.9195794,0.0008626344,0.07809407,0.00001248333,0.0002897921],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001309787,0.0005018689,0.9969652,0.00001532931,0.0001875571,0.0006549177,0.00001902202,0.00003364501,0.0003126571],"genre_scores_gemma":[0.7659595,3.868102e-7,0.2334419,0.00001825191,0.0004536582,0.00005175109,0.00005036861,0.0000214789,0.000002740828],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7646497,"threshold_uncertainty_score":0.99992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08116319810565686,"score_gpt":0.3790989084629166,"score_spread":0.2979357103572597,"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."}}