Biodiversity and ecosystem functioning: reconciling the results of experimental and observational studies
Bibliographic record
Abstract
Biodiversity and ecosystem functioning research has been some of the most controversial of the last decade but rapid progress has been made by deriving hypotheses from the differing view points and challenging them with appropriate experimental and analytical tests (Loreau et al. 2001). Here we address some recent criticisms of the BIODEPTH project (Thompson et al. 2005) and show that: 1. While legume species play an important role in the BIODEPTH results, patterns are not generally consistent with the multispecies sampling effect for legumes proposed by Huston & McBride (2002) as suggested in Thompson et al. (2005). 2. The BIODEPTH results are also not consistent with transient biodiversity effects. Levels of species diversity were generally maintained over the 3 years of the project (i.e. little competitive exclusion) and diversity-productivity relationships in BIODEPTH generally strengthened during the experiments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.082 | 0.162 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.005 | 0.012 |
| Open science | 0.008 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".