{"id":"W4399884548","doi":"10.1016/j.tpb.2024.06.003","title":"Stochastic viability in an island model with partial dispersal: Approximation by a diffusion process in the limit of a large number of islands","year":2024,"lang":"en","type":"article","venue":"Theoretical Population Biology","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Population; Markov chain; Mathematics; Statistics; Biological dispersal; Fixation (population genetics); Population model; Markov process; Covariance; Statistical physics; Ergodicity; Applied mathematics; Physics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001267706,0.0008033962,0.001493924,0.001275143,0.0008449386,0.002372953,0.002865803,0.002615338,0.002312713],"category_scores_gemma":[0.006502452,0.0007443363,0.00115285,0.0008068825,0.003034289,0.003071437,0.00181879,0.001712466,0.0004003883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001622652,"about_ca_system_score_gemma":0.001018188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01514364,"about_ca_topic_score_gemma":0.006206701,"domain_scores_codex":[0.9996738,0.0001207201,0.00001604919,0.00005870213,0.0000577549,0.00007289091],"domain_scores_gemma":[0.996932,0.001773547,0.0004137103,0.0001417295,0.0003148121,0.0004241802],"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":[0.00007608219,0.00005565384,0.002421026,0.00009332521,0.00006248373,0.0005132532,0.0002154021,0.7264379,0.00219009,0.2643109,0.001426147,0.002197827],"study_design_scores_gemma":[0.00001343549,0.000009455674,0.0001976945,0.000006508882,0.000008873513,0.0000469768,0.00002172876,0.9771183,0.00004603406,0.02238013,0.0001393502,0.0000115133],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5599977,0.002207075,0.4123102,0.004407208,0.0002185042,0.00006405658,0.0002884899,0.0002965053,0.02021028],"genre_scores_gemma":[0.9800249,0.0006903055,0.00776317,0.0001663789,0.0001061692,0.00005284634,0.0001154478,0.00008749851,0.01099332],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01514364,"threshold_uncertainty_score":0.03011096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005695213169609609,"score_gpt":0.2970908024759176,"score_spread":0.2913955893063079,"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."}}