Allelopathic effect of <i>Salix caprea</i> litter on late successional plants at different substrates of post-mining sites: pot experiment studies
Bibliographic record
Abstract
The willow Salix caprea L. is a common colonizer of post-mining sites including those in the Sokolov coal mining district (Czech Republic) where this study was conducted. In one bioassay and two pot experiments, we investigated the effect of S. caprea litter on three plant species ( Arrhenatherum elatius (L.) P. Beauv. ex J. Presl & C. Presl, Plantago lanceolata L., and Lotus corniculatus L.) that commonly grow in late successional stages on these sites. In a sandy soil, leachate from fresh S. caprea litter reduced the number of germinated individuals (experiment 1) and shoot and root growth (experiment 2). In the clayey substrate originally unaffected by the S. caprea (experiment 3) leachate suppressed germination of all three species, but no reduction of biomass (both aboveground and belowground) was observed. Biomass was enhanced, however, in substrate that was naturally enriched with S. caprea litter (i.e., substrate collected on the same locality as previously mentioned substrate but beneath the S. caprea shrubs). Salix caprea therefore can suppress the establishment of new plants that arrive as seeds, but this suppression may only occur with seeds that directly contact the litter. When S. caprea litter is incorporated into the substrate, it can considerably improve substrate quality and the growth of successional plants.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".