Relative competitive performance of 63 species of terrestrial herbaceous plants
Why this work is in the frame
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Bibliographic record
Abstract
Abstract. There is growing evidence that plant and animal species are arranged in hierarchies of relative competitive performance. More work is needed to determine which plant traits best predict relative competitive performance. We therefore measured relative competitive performance of 63 terrestrial herbaceous plant species using Trichostema brachiatum as a reference species (that is, phytometer or target species). The neighbour species came from a wide array of terrestrial vegetation types (e.g. rock barrens, alvars, old fields), and represented a wide array of growth forms (e.g. small rosette species such as Saxifraga virginiensis and large clonal graminoids such as Agropyron repens ). The experiment was repeated with two pot sizes: large (control) and small (stress treatment). Relative competitive performance in large pots (controls) was highly correlated with that in small pots (stress treatment) ( r = 0.90, p < 0.001). The hierarchy of relative competitive performance in the large pots was also highly correlated with the hierarchy in the small (stressed) pots ( r s = 0.91, p < 0.001). Principal components analysis and multiple linear regression showed that plant size (measured by total biomass, above‐ground biomass, below‐ground biomass, canopy area, height and leaf area index) and leaf shape (measured as length to width ratio, length, width) were the two characteristics that best predicted relative competitive performance (large pots, r 2 = 0.55; small pots, r 2 = 0.48).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it