Bibliographic record
Abstract
We investigated the relative contributions of size and growth form (biomass allocation) to competitive effects between grasses and shrubs in western Canada for two years. We measured the effects of grasses and shrubs on each other at the population level using removal experiments in natural vegetation. In prairie where shrub abundance was low, shrubs suppressed grasses as much as grasses suppressed shrubs, even though shrubs had six times more standing crop. In adjacent brush clumps, however, where shrub standing crop was 37 times grass standing crop, shrubs suppressed grasses strongly, whereas grasses did not suppress shrubs. Shrubs reduced available soil nitrogen more strongly than grasses did, but shrubs and grasses did not differ in their effects on light or soil water. On a per‐gram basis, however, shrubs had smaller effects on light, nitrogen, and water consumption than grasses did. In spite of their smaller per‐gram effects on resources, the secondary growth of shrubs allowed them to accumulate more mass and height, and to eventually displace grasses. During this process, competition between the woody and the herbaceous growth form changed from symmetric to asymmetric.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".