{"id":"W2027210102","doi":"10.1098/rstb.2008.0286","title":"Predicting invasion success in complex ecological networks","year":2009,"lang":"en","type":"article","venue":"Philosophical Transactions of the Royal Society B Biological Sciences","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":198,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Intel Corporation; International Business Machines Corporation; National Science Foundation","keywords":"Trophic level; Ecology; Biology; Generalist and specialist species; Predation; Range (aeronautics); Ecological network; Population; Generality; Food web; Invasive species; Niche; Omnivore; Introduced species; Habitat; Community; Herbivore; Ecosystem","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":[0.001860553,0.0007677499,0.0004023669,0.001569233,0.0003450352,0.001068199,0.0005562559,0.0007987303,0.0008629456],"category_scores_gemma":[0.008851416,0.0004735143,0.0005932469,0.0005526151,0.0005897993,0.001480909,0.0008007617,0.000575455,0.0002294686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009046968,"about_ca_system_score_gemma":0.0003505305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01463534,"about_ca_topic_score_gemma":0.01399288,"domain_scores_codex":[0.9996065,0.0001997577,0.00002527061,0.00009006961,0.0000357862,0.00004264153],"domain_scores_gemma":[0.9939771,0.004690927,0.0007019959,0.0002013972,0.0002197404,0.000208921],"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":[0.00003338124,0.00002166703,0.0437732,0.00001330233,0.00004266737,0.0000273675,0.00003789548,0.9526615,0.0002517523,0.0003939993,0.0001010452,0.002642349],"study_design_scores_gemma":[0.000002327692,0.00001170059,0.002697482,0.000002704432,0.000004740772,0.00001205206,0.00001124486,0.9965566,0.00006163465,0.0005878164,0.0000486766,0.000002989402],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9818356,0.0001139151,0.01690079,0.0001487027,0.000007843204,0.00001848052,0.0001471947,0.0001433194,0.0006840876],"genre_scores_gemma":[0.991936,0.00009250065,0.007411282,0.0000163338,0.000005431616,0.00001706154,0.0002025655,0.00001417228,0.0003046158],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01463534,"threshold_uncertainty_score":0.0291003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1079198822183209,"score_gpt":0.2557360160131061,"score_spread":0.1478161337947852,"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."}}