{"id":"W659103082","doi":"10.1016/j.ecolmodel.2015.04.026","title":"The application of life-history and predation allometry to population dynamics to predict the critical density of extinction","year":2015,"lang":"en","type":"article","venue":"Ecological Modelling","topic":"Aquatic Invertebrate Ecology and Behavior","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Allometry; Extinction (optical mineralogy); Predation; Ecology; Density dependence; Population; Extinction probability; Functional response; Population density; Biology; Population size; Predator; 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":[0.001043973,0.000374348,0.0003087399,0.0006058886,0.0005461429,0.0007363275,0.0007531989,0.0007262345,0.0008144939],"category_scores_gemma":[0.004118896,0.0004121774,0.0006158195,0.0003057113,0.0006098183,0.0007836873,0.0005077667,0.0006305817,0.0001545475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009276571,"about_ca_system_score_gemma":0.0004671915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01073215,"about_ca_topic_score_gemma":0.007552614,"domain_scores_codex":[0.9999052,0.00004861084,0.000006286515,0.00001791907,0.00001048348,0.00001137859],"domain_scores_gemma":[0.9984816,0.001144025,0.0001491825,0.00006962292,0.00007666655,0.00007899437],"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":[0.00001689777,0.00002964131,0.01251237,0.000009671074,0.00004026085,0.00001823318,0.00004196267,0.9805763,0.000588314,0.002116165,0.0001029514,0.003947177],"study_design_scores_gemma":[0.000001240461,0.000003581345,0.0009939986,7.733916e-7,0.000002728865,0.000007822242,0.000002765024,0.9979383,0.00004079053,0.0009828658,0.00002305874,0.000001907407],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9087204,0.0002033182,0.08842541,0.0003121969,0.00002495573,0.00001617566,0.00006928161,0.00007460706,0.002153629],"genre_scores_gemma":[0.9925119,0.00006917611,0.006816523,0.00002145174,0.00001194396,0.00001373219,0.00002642394,0.00001601733,0.0005129439],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01073215,"threshold_uncertainty_score":0.02133936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03731081051943769,"score_gpt":0.2508219262387775,"score_spread":0.2135111157193398,"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."}}