{"id":"W1995339116","doi":"10.1111/1365-2664.12376","title":"Pathway‐level models to predict non‐indigenous species establishment using propagule pressure, environmental tolerance and trait data","year":2014,"lang":"en","type":"article","venue":"Journal of Applied Ecology","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Propagule pressure; Trait; Proxy (statistics); Propagule; Environmental data; Biology; Indigenous; Ecology; Statistical model; Econometrics; Statistics; Computer science; Mathematics; Population; Demography; Biological dispersal","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":[0.003232731,0.0007511925,0.0007847157,0.001054542,0.0004392974,0.001230108,0.001998295,0.001057176,0.005125465],"category_scores_gemma":[0.006286222,0.0005999829,0.001737182,0.0008533465,0.0005886116,0.001074948,0.001232831,0.001445789,0.0006262031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001647047,"about_ca_system_score_gemma":0.001893358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0298417,"about_ca_topic_score_gemma":0.02264707,"domain_scores_codex":[0.9994687,0.0002373164,0.0000333478,0.0001567957,0.00004547596,0.00005829404],"domain_scores_gemma":[0.9956977,0.003074703,0.0004797436,0.0001735367,0.0003918945,0.0001823056],"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":[0.00006173777,0.00004910691,0.02397461,0.0001161084,0.0001595578,0.00005796375,0.0001052358,0.9573933,0.0003785704,0.00519556,0.0008407305,0.01166765],"study_design_scores_gemma":[0.000007755274,0.00002921846,0.003011342,0.00001585204,0.00003363736,0.00001125246,0.00002445075,0.9919626,0.00006138786,0.004349885,0.0004812127,0.00001151606],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4722346,0.001421491,0.5157063,0.001481336,0.0001534501,0.0002110941,0.003823416,0.00104554,0.003922721],"genre_scores_gemma":[0.9506423,0.0006190535,0.04328626,0.0001398763,0.00005517616,0.0003288016,0.001434541,0.00007585152,0.003418037],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0298417,"threshold_uncertainty_score":0.05933601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05343105162937842,"score_gpt":0.2310001805233971,"score_spread":0.1775691288940187,"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."}}