{"id":"W2768902011","doi":"10.1111/ddi.12681","title":"The rich get richer: Invasion risk across North America from the aquarium pathway under climate change","year":2017,"lang":"en","type":"article","venue":"Diversity and Distributions","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Geological Survey","keywords":"Propagule pressure; Climate change; Climate change scenario; Geography; Ecology; Risk assessment; Environmental science; Environmental resource management; Fishery; Biology; Biological dispersal; Economics; Demography; Population","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0001663301,0.0000787374,0.0000689908,0.000002147889,0.02440882,0.00008723549,0.0003806484,0.00003542121,0.00006994852],"category_scores_gemma":[0.00008860042,0.00004874622,0.00003300323,0.00004766407,0.0009106647,0.0002182755,0.004599346,0.0001195723,0.0001999103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004108033,"about_ca_system_score_gemma":0.000001363858,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004330904,"about_ca_topic_score_gemma":0.03403255,"domain_scores_codex":[0.9993624,0.00005420716,0.00005721905,0.0001818123,0.0001005096,0.0002438616],"domain_scores_gemma":[0.9993905,0.0001429059,0.0001059645,0.0003145818,0.000007119043,0.00003887296],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009890332,0.0000329875,0.9858853,6.397756e-7,0.00002511676,0.000001852274,0.001302786,0.000009843778,3.986611e-7,0.0002343429,0.0112542,0.001242705],"study_design_scores_gemma":[0.0001608249,0.00001636267,0.9698715,0.000001304939,0.00004237,1.167294e-7,0.001766793,0.00005902888,0.00000223597,0.0009353595,0.02707635,0.00006780913],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9894582,0.00004216574,0.0004447239,0.006125968,0.0001457733,0.0001622983,0.001698324,0.00002061973,0.001901905],"genre_scores_gemma":[0.9972212,0.0019633,0.00000889489,0.0005888705,0.00002873651,0.0000118124,0.00008822992,0.000001460809,0.00008744065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02970165,"threshold_uncertainty_score":0.9835938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02932759015989334,"score_gpt":0.2294004111239523,"score_spread":0.200072820964059,"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."}}