{"id":"W2045967620","doi":"10.1093/imammb/dqi003","title":"A multi-species epidemic model with spatial dynamics","year":2005,"lang":"en","type":"article","venue":"Mathematical Medicine and Biology A Journal of the IMA","topic":"Mathematical and Theoretical Epidemiology and Ecology Models","field":"Medicine","cited_by":156,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Basic reproduction number; Digraph; Component (thermodynamics); Epidemic model; Disease transmission; Computation; Stability (learning theory); Transmission (telecommunications); Biology; Ecology; Mathematics; Computer science; Combinatorics; Physics; Algorithm; Virology; Demography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009952665,0.001008035,0.001438881,0.001018721,0.0009513322,0.002312254,0.00267299,0.003329005,0.005567506],"category_scores_gemma":[0.002399863,0.0005616037,0.001150555,0.002018083,0.001032586,0.002409206,0.001339592,0.001514085,0.001066944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00111292,"about_ca_system_score_gemma":0.001098471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006614957,"about_ca_topic_score_gemma":0.003698501,"domain_scores_codex":[0.9993036,0.0002354055,0.00005338947,0.0001644993,0.0001265014,0.0001166552],"domain_scores_gemma":[0.9989579,0.0005196572,0.0001742617,0.0000766974,0.0001452578,0.0001262401],"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":[0.0001215221,0.0001344738,0.002038423,0.0002188129,0.00009806773,0.001659059,0.0003930929,0.7766918,0.00224749,0.203001,0.003749644,0.009646575],"study_design_scores_gemma":[0.00006290721,0.0000747492,0.0003452784,0.00001891916,0.00004627543,0.0003293163,0.00006144622,0.9617992,0.0001551039,0.03108588,0.005994251,0.00002660671],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1706875,0.00325987,0.7646694,0.005364547,0.0006611273,0.0004867661,0.003263849,0.0009080503,0.05069899],"genre_scores_gemma":[0.871265,0.002755826,0.0774636,0.0006481477,0.0003882872,0.0007296058,0.0009414696,0.00009770628,0.04571049],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006614957,"threshold_uncertainty_score":0.0186252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07334427910555277,"score_gpt":0.3369944462435102,"score_spread":0.2636501671379574,"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."}}