{"id":"W4408919450","doi":"10.1016/j.biocontrol.2025.105754","title":"Predicting the potential distribution of the invasive weed Mikania micrantha and its biological control agent Puccinia spegazzinii under climate change scenarios in China","year":2025,"lang":"en","type":"article","venue":"Biological Control","topic":"Biological Control of Invasive Species","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trinity Western University; Western University","funders":"National Key Research and Development Program of China; Ten Thousand Talent Plans for Young Top-notch Talents of Yunnan Province; National Office for Philosophy and Social Sciences; National Natural Science Foundation of China","keywords":"Mikania micrantha; Biology; Weed; Biological pest control; Invasive species; Weed control; China; Puccinia; Agronomy; Ecology; Botany; Geography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0004164443,0.0006559379,0.0003243938,0.000753594,0.0003807507,0.0005682172,0.0005575973,0.0005256532,0.0003479585],"category_scores_gemma":[0.0006354988,0.0002907346,0.0006491294,0.000617205,0.0003067226,0.0005644804,0.0003493107,0.0002519671,0.00006411953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001494429,"about_ca_system_score_gemma":0.0009402695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1027192,"about_ca_topic_score_gemma":0.05944868,"domain_scores_codex":[0.9998966,0.00001737652,0.000006485743,0.00002856834,0.00001991248,0.00003099988],"domain_scores_gemma":[0.9997808,0.00007162391,0.00004352101,0.00001461321,0.0000482111,0.0000411109],"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":[0.00006405608,0.0000493315,0.07852139,0.00002873743,0.00005390792,0.0002798164,0.00006248897,0.9129734,0.00250069,0.0002163339,0.0002714459,0.004978294],"study_design_scores_gemma":[0.00000884386,0.00001953612,0.03252714,0.000002544497,0.00001648566,0.00001938477,0.00004700298,0.9666449,0.0004324236,0.0001376992,0.0001343716,0.000009696042],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984622,0.00005971091,0.0008106283,0.00006931978,0.000002993936,0.000006670002,0.0001778831,0.00003606587,0.0003745895],"genre_scores_gemma":[0.999009,0.00006471558,0.0005071233,0.000007020734,0.000001931722,0.000004994039,0.000252792,0.000003595261,0.0001488104],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1027192,"threshold_uncertainty_score":0.2042426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02655661552579398,"score_gpt":0.2196053309884201,"score_spread":0.1930487154626261,"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."}}