{"id":"W2363321137","doi":"10.1002/ecy.1460","title":"Effects of functional diversity loss on ecosystem functions are influenced by compensation","year":2016,"lang":"en","type":"article","venue":"Ecology","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"National Natural Science Foundation of China; Chinese Academy of Sciences; National Science Foundation","keywords":"Biodiversity; Ecosystem; Ecology; Biology; Biomass (ecology); Ecosystem services; Foundation species; Ecosystem diversity; Productivity; Perennial plant; Ecological stability","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":[0.0006527251,0.0003405727,0.0003475116,0.000467716,0.0002329843,0.0004346802,0.0002716589,0.0004180279,0.0007851626],"category_scores_gemma":[0.001293961,0.0001451324,0.0002551103,0.0001721029,0.0005517795,0.0003515406,0.0006624666,0.0004643566,0.0001122727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00040932,"about_ca_system_score_gemma":0.0001626512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001580788,"about_ca_topic_score_gemma":0.00146809,"domain_scores_codex":[0.9996911,0.0000842298,0.00002484032,0.00005163286,0.00006349794,0.00008474595],"domain_scores_gemma":[0.9984146,0.0003740132,0.0004472435,0.0002363356,0.0001869745,0.0003407069],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001387319,0.000255305,0.2700015,0.0001318501,0.0004196189,0.0004141332,0.0002274228,0.008723947,0.7030319,0.0003237495,0.0002383086,0.01484491],"study_design_scores_gemma":[0.000007965117,0.0003745964,0.981528,0.000005305685,0.00002983612,0.000185764,0.0001097635,0.0061646,0.01104489,0.0002841955,0.0002529233,0.00001208142],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99926,0.00009192506,0.0002990092,0.00001970999,0.000002222918,0.000003392088,0.00003756882,0.00000844125,0.0002777149],"genre_scores_gemma":[0.9997738,0.00001375438,0.00007450888,0.00001595643,0.000001019407,0.000002741069,0.00003954273,0.000001697446,0.00007686796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001580788,"threshold_uncertainty_score":0.003452003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005511699549456803,"score_gpt":0.1865488548975268,"score_spread":0.18103715534807,"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."}}