Fingerprint Composition of Seedling Root Exudates of Selected Grasses
Bibliographic record
Abstract
The competitiveness of plants within a community is dictated to some extent by their association with microorganisms in the soil. That association is affected by root exudates and possibly by their quality. The competitiveness of species under various grazing regimes has been defined by their response to grazing as decreaser, increaser, or invader. To test the hypothesis that there are recognisable differences in the chemical fingerprints of the root exudates of decreasers, increasers and invaders, seeds of 8 grasses, representing these 3 designations, were germinated and grown for 2 weeks in a root exudate trapping system in the laboratory. Tentative identification of the suite of compounds recovered from the root exudates by a solvent extraction technique was done with the help of gas chromatography/mass spectrometry and authentic samples. Eleven identified compounds, present in all exudates as major peaks, but absent in the blanks, were selected for semi-quantitatively comparing the 3 grazing response groups. For all 11 compounds, there was always at least 1 of the grazing response groups that had the highest percentages. That is to say, they were qualitatively, based on the 11 compounds selected, but not quantitatively similar.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".