{"id":"W4409421084","doi":"10.1002/mma.10963","title":"Disease Transmission on Random Graphs Using Edge‐Based Percolation","year":2025,"lang":"en","type":"article","venue":"Mathematical Methods in the Applied Sciences","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Percolation (cognitive psychology); Random graph; Enhanced Data Rates for GSM Evolution; Transmission (telecommunications); Statistical physics; Combinatorics; Graph; Artificial intelligence; Telecommunications; Physics; Computer 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001669249,0.0005884051,0.0007033988,0.002776649,0.0005456426,0.001687141,0.001422264,0.001108661,0.004354356],"category_scores_gemma":[0.008352485,0.000421917,0.001173007,0.001540415,0.001185918,0.002792111,0.001457155,0.001003213,0.0006454865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001111348,"about_ca_system_score_gemma":0.0005306891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004424619,"about_ca_topic_score_gemma":0.003130046,"domain_scores_codex":[0.9987948,0.0007189072,0.00004340223,0.0001980333,0.0001670224,0.00007772703],"domain_scores_gemma":[0.9962101,0.00293876,0.0003590714,0.0002115846,0.0001720978,0.0001083771],"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":[0.0000428228,0.00004889175,0.002923525,0.0001905191,0.0001138805,0.0002709458,0.0001775926,0.6370305,0.002061263,0.3422082,0.002796567,0.0121353],"study_design_scores_gemma":[0.00000789346,0.00001175541,0.0004125885,0.00002258875,0.00001495606,0.00007931714,0.00001817334,0.8661376,0.0002173007,0.1320083,0.001053873,0.00001574855],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05725975,0.0009103724,0.9297337,0.0008700374,0.00007152811,0.0001063892,0.0006753903,0.0005070949,0.009865666],"genre_scores_gemma":[0.8738894,0.001320404,0.1186435,0.0002587266,0.0001323722,0.0001960673,0.000375576,0.0002414686,0.004942563],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004424619,"threshold_uncertainty_score":0.01456678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06333096638941675,"score_gpt":0.429144680475707,"score_spread":0.3658137140862903,"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."}}