{"id":"W2007870229","doi":"10.1098/rspb.2013.1747","title":"Stochastic environmental fluctuations drive epidemiology in experimental host–parasite metapopulations","year":2013,"lang":"en","type":"article","venue":"Proceedings of the Royal Society B Biological Sciences","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Agence Nationale de la Recherche","keywords":"Metapopulation; Parasite hosting; Biology; White noise; Host (biology); Noise (video); Permissive; Ecology; Population; Statistics; Mathematics; Genetics; 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":[0.0009073819,0.0002658402,0.0003458388,0.0003086413,0.0002302552,0.0004534936,0.0005307115,0.0003863266,0.0005022551],"category_scores_gemma":[0.002561207,0.0002597039,0.0003073654,0.0002471393,0.0004589785,0.0003778313,0.0003842928,0.0006515709,0.00009434586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006668268,"about_ca_system_score_gemma":0.0002747214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00110147,"about_ca_topic_score_gemma":0.00169832,"domain_scores_codex":[0.9992478,0.0003956619,0.00008456614,0.0001239974,0.00008692491,0.00006104632],"domain_scores_gemma":[0.9978551,0.0009469366,0.0005737168,0.0003723486,0.00009445319,0.0001574365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001332743,0.001555928,0.08547252,0.0003230986,0.0003003179,0.0002749083,0.0004796672,0.1090876,0.7810307,0.008457669,0.0003842553,0.01130056],"study_design_scores_gemma":[0.0003369969,0.004155086,0.09164716,0.00006783192,0.00018765,0.0003122479,0.00024838,0.7541868,0.135097,0.0118636,0.001797697,0.00009953897],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961358,0.00005245617,0.003410927,0.00004789494,0.000006107571,0.00002013054,0.00008792643,0.00002257078,0.0002162935],"genre_scores_gemma":[0.9962368,0.00007497246,0.003317987,0.00003080945,0.000004357125,0.00005908809,0.0001153378,0.00001079198,0.0001497912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00110147,"threshold_uncertainty_score":0.004838169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0227259593992301,"score_gpt":0.279896779719788,"score_spread":0.2571708203205579,"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."}}