{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009314669,0.00006458104,0.0001141842,0.0000271678,0.0002726145,0.000001123808,0.00006665416,0.00006538654,0.000717464],"category_scores_gemma":[0.00008971337,0.00004874273,0.00002946011,0.00006457475,0.000161324,0.00008792323,0.0001496147,0.00004346936,0.0009652288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001495264,"about_ca_system_score_gemma":0.000004070293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001387136,"about_ca_topic_score_gemma":0.001249508,"domain_scores_codex":[0.999445,0.00008115792,0.0001103558,0.0001637221,0.00008164821,0.0001180815],"domain_scores_gemma":[0.999274,0.0004950156,0.0001177991,0.00007108922,0.00001473066,0.0000273361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003486618,0.0000965759,0.9912521,0.000008566965,0.0000264105,0.000002007386,0.00006136724,0.0006327371,0.003329571,0.0004571049,0.003956939,0.0001417031],"study_design_scores_gemma":[0.0005230838,0.0001496752,0.9978899,0.000006120118,0.00001330013,0.000001518346,0.00002039733,0.00006992328,0.0005140699,0.0003786194,0.0003772721,0.00005615683],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964226,0.000003617551,0.0009737742,0.0007265847,0.0004143975,0.0001334172,0.00001918004,0.00002023288,0.001286153],"genre_scores_gemma":[0.9987647,0.000009214549,0.00001310316,0.0002062484,0.00001164456,0.00001958326,0.000004043843,0.000002638014,0.0009688073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006637713,"threshold_uncertainty_score":0.9998127,"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."}}