{"id":"W4413403972","doi":"10.1111/nph.70468","title":"Responses to climate change – insights and limitations from herbaceous plant model species","year":2025,"lang":"en","type":"article","venue":"New Phytologist","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Division of Environmental Biology; Division of Integrative Organismal Systems; Natural Sciences and Engineering Research Council of Canada; National Institute of Food and Agriculture; U.S. Department of Energy","keywords":"Ecology; Climate change; Biological dispersal; Biology; Maladaptation; Habitat; Herbaceous plant; Forb; Population; Demography","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":[0.001658932,0.0003521019,0.0007199041,0.0002861564,0.0004276908,0.0008092503,0.001087339,0.0004050027,0.001269748],"category_scores_gemma":[0.001604635,0.0001793413,0.0005168267,0.000459163,0.0004299941,0.001133405,0.0006774224,0.0007983788,0.0003221544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006152792,"about_ca_system_score_gemma":0.0004235263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003878275,"about_ca_topic_score_gemma":0.006662427,"domain_scores_codex":[0.9998115,0.00009955611,0.0000149431,0.00004128633,0.00001952284,0.00001330493],"domain_scores_gemma":[0.9989811,0.0007433458,0.0000652352,0.00008851763,0.00007406908,0.0000477745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001437878,0.000537304,0.1290078,0.008159285,0.002094215,0.001153461,0.004506936,0.2771808,0.1152606,0.1151246,0.018147,0.3273903],"study_design_scores_gemma":[0.0002786388,0.001505377,0.1473105,0.001882286,0.001616796,0.001162518,0.003355605,0.3633823,0.01293216,0.2618091,0.204442,0.0003227183],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8583307,0.04275934,0.06116357,0.005438961,0.0002259416,0.0001185912,0.003798911,0.0003485946,0.02781549],"genre_scores_gemma":[0.9449768,0.02532984,0.02397763,0.001676345,0.00009120622,0.0002409389,0.002183955,0.0001246071,0.0013987],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003878275,"threshold_uncertainty_score":0.008773386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09477400492605768,"score_gpt":0.2833295854138815,"score_spread":0.1885555804878238,"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."}}