{"id":"W2125952937","doi":"10.1109/cec.2008.4630866","title":"Behavioral regimes in the evolution of extremal epidemic graphs","year":2008,"lang":"en","type":"article","venue":"","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"University of Guelph","keywords":"Population; Degree (music); Sequence (biology); Computer science; Operator (biology); Degree distribution; Chromosome; Representation (politics); Evolutionary algorithm; Population size; Complex network; Theoretical computer science; Artificial intelligence; Biology; Demography","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":[],"consensus_categories":[],"category_scores_codex":[0.0001699836,0.00006471703,0.0001326087,0.00007859452,0.00004218626,0.000003032918,0.0001627962,0.00001556987,0.0002114043],"category_scores_gemma":[0.000001102612,0.00004460274,0.0001142848,0.0003074435,0.00006420165,0.00005430177,0.0000239612,0.0000828062,0.000003235799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001659184,"about_ca_system_score_gemma":0.00001952669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004314217,"about_ca_topic_score_gemma":0.00008787784,"domain_scores_codex":[0.9994194,0.00006911709,0.0001969413,0.0001016688,0.00009968774,0.0001131904],"domain_scores_gemma":[0.9996252,0.00004487257,0.00006820653,0.0002264168,0.00002345764,0.00001185228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003843475,0.0001477324,0.8382742,7.752239e-7,0.000009189481,9.125045e-7,0.0002292636,0.0000229367,0.0002958627,0.1533083,0.005040136,0.002666777],"study_design_scores_gemma":[0.0006839432,0.0001803646,0.7114168,0.00004547148,0.0001275932,0.00001023797,0.003375519,0.005256736,0.00266067,0.2730117,0.002755546,0.0004753727],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9700072,0.00007438033,0.01052584,0.00006257814,0.000008875409,0.00009617174,0.000001384604,0.00002248511,0.01920104],"genre_scores_gemma":[0.9985355,0.000002629359,0.001123292,0.000009153683,0.00003704095,0.00001532547,0.000006252039,0.000003720274,0.0002671486],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1268574,"threshold_uncertainty_score":0.6521834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03159807849730051,"score_gpt":0.2912098592077597,"score_spread":0.2596117807104592,"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."}}