{"id":"W2767812464","doi":"10.1109/tnet.2019.2940888","title":"Curing Epidemics on Networks Using a Polya Contagion Model","year":2019,"lang":"en","type":"preprint","venue":"IEEE/ACM Transactions on Networking","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Queen's University","keywords":"Curing (chemistry); Computer science; Mathematical optimization; Gradient descent; Network structure; Operations research; Mathematics; Artificial intelligence; Distributed computing; Artificial neural network; Materials science","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","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0005935014,0.00102814,0.001281532,0.0005037496,0.0005903654,0.0002744558,0.001104837,0.0005570907,0.000111815],"category_scores_gemma":[0.000002850623,0.001157331,0.00118589,0.0005052753,0.00008226878,0.0001444075,0.0001062486,0.003429759,0.00002384377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004922678,"about_ca_system_score_gemma":0.0001916546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005581442,"about_ca_topic_score_gemma":0.00004613654,"domain_scores_codex":[0.9955977,0.0002637285,0.001106239,0.001428398,0.0005210081,0.001082949],"domain_scores_gemma":[0.9959966,0.0005052091,0.0007937957,0.002346923,0.0001354924,0.0002220076],"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":[0.00007945691,0.0001768624,0.0008256029,0.00002800265,0.0004997898,0.000002708593,0.00008399167,0.9550414,0.0000391966,0.0004151396,0.0003707882,0.04243706],"study_design_scores_gemma":[0.000375171,0.00005185698,0.00001512557,0.001529113,0.0005311529,0.000001946597,0.00002904731,0.9823101,0.0002567639,0.01319442,0.0007116345,0.0009936856],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02165769,0.0002775348,0.9717358,0.0001104615,0.002732392,0.0009716294,0.00006173625,0.000458136,0.001994653],"genre_scores_gemma":[0.98255,0.0001826727,0.01273168,0.0002875903,0.003457834,0.0001500367,0.0001105649,0.0002326768,0.0002969285],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9608923,"threshold_uncertainty_score":0.9990877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06640543453596294,"score_gpt":0.3193502258574131,"score_spread":0.2529447913214502,"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."}}