{"id":"W2604534264","doi":"10.1002/ecs2.1731","title":"Climatic suitability ranking of biological control candidates: a biogeographic approach for ragweed management in Europe","year":2017,"lang":"en","type":"article","venue":"Ecosphere","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"UC Berkeley College of Chemistry; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Florida Department of Agriculture and Consumer Services; Russian Academy of Sciences; Université de Fribourg; University of California Berkeley; University of Alberta; Florida Museum of Natural History; National Science Foundation","keywords":"Ragweed; Ambrosia artemisiifolia; Invasive species; Range (aeronautics); Ecology; Niche; Environmental niche modelling; Biodiversity; Biology; Ecological niche; Introduced species; Habitat; Biological pest control; Geography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001171328,0.0005037587,0.0005416059,0.006309807,0.0004630377,0.0011761,0.0004485099,0.0003651087,0.001260058],"category_scores_gemma":[0.001845586,0.0001771538,0.001011437,0.002373775,0.0003775978,0.0004883047,0.0008535246,0.0002581321,0.0001424093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004437947,"about_ca_system_score_gemma":0.0003728943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007455525,"about_ca_topic_score_gemma":0.00898785,"domain_scores_codex":[0.9992731,0.0003433241,0.00006309035,0.000174891,0.00006748277,0.00007816293],"domain_scores_gemma":[0.9983669,0.000738417,0.0004310103,0.00007520616,0.0002409682,0.0001475962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000187314,0.00009037103,0.9567523,0.00007455031,0.0003809555,0.0002421161,0.0002446052,0.01809946,0.005411133,0.0003852873,0.000191364,0.01794051],"study_design_scores_gemma":[0.00002600997,0.0001816635,0.8777621,0.00002588229,0.0001719604,0.0001722532,0.001067383,0.1187567,0.0007313247,0.000494844,0.0005863072,0.00002347063],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917876,0.0002462169,0.006440914,0.00005260165,0.00000356655,0.00003950615,0.0003752008,0.00004777747,0.001006619],"genre_scores_gemma":[0.9954045,0.00004631466,0.004048461,0.000007366568,0.000006083708,0.00002366124,0.0003778419,0.000007276733,0.00007855619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007455525,"threshold_uncertainty_score":0.01482427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03499691610853665,"score_gpt":0.2609758609005057,"score_spread":0.2259789447919691,"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."}}