{"id":"W2974153520","doi":"10.1111/1365-2435.13459","title":"Functional diversity enhances, but exploitative traits reduce tree mixture effects on microbial biomass","year":2019,"lang":"en","type":"article","venue":"Functional Ecology","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biology; Biomass (ecology); Biodiversity; Ecosystem; Functional diversity; Species richness; Specific leaf area; Monoculture; Ecology; Botany; Agronomy","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001606257,0.0001904095,0.0002166362,0.00007171327,0.0005530631,0.000007252106,0.0001348309,0.0002035179,0.007858326],"category_scores_gemma":[0.00008058233,0.0001812903,0.0000969447,0.0001686735,0.0002464371,0.0001679622,0.0002844682,0.0002363329,0.006976402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002938077,"about_ca_system_score_gemma":0.00002873697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002126329,"about_ca_topic_score_gemma":0.0009869017,"domain_scores_codex":[0.9986755,0.0001409022,0.0001627396,0.0005045965,0.0002062148,0.0003100398],"domain_scores_gemma":[0.999005,0.0006847155,0.0001086939,0.0001022344,0.00003002613,0.00006931225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001756197,0.0009028275,0.5664841,0.00006118187,0.0005146006,0.00004168016,0.001244844,0.004380986,0.2779857,0.005633252,0.13731,0.00368462],"study_design_scores_gemma":[0.001110269,0.0005645887,0.9898068,0.000004842105,0.00002811623,0.00001530012,0.0001100885,0.00009049228,0.004259214,0.002055172,0.001760131,0.0001949426],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9814795,0.00001497526,0.0003550258,0.00122007,0.002768138,0.0003035743,0.00002455647,0.00004977602,0.01378442],"genre_scores_gemma":[0.9827123,0.000004888778,0.0003063173,0.001508693,0.0001747932,0.00005327847,0.00007466497,0.00001000415,0.01515501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4233227,"threshold_uncertainty_score":0.9937968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01003360215048827,"score_gpt":0.2024454224973455,"score_spread":0.1924118203468572,"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."}}