N-alkane profiles of common rangeland species in northern China and the influence of drying method on their concentrations
Bibliographic record
Abstract
Plant wax alkanes have been used as internal markers to estimate diet composition of grazing animals. However, alkane contents in samples may vary depending on the drying method used. This study was undertaken to determine the alkane profiles and concentrations of 17 common range land species in northern China with two different drying methods. The results showed that regardless of drying methods, the odd-chain alkanes, particular C29 and C33, predominated in cuticular wax in all 17 common species and their component plant parts. The alkane patterns of plant species within the same genus were relatively similar and the differences in alkanes between stem and leaf were generally smaller than those between inflorescences and leaf or stem. The influence of drying methods on alkane concentrations varied depending on family and individual alkane. The effect of drying methods on C29 seemed to be smaller than other alkanes in all the samples. The oven-dry method produced higher concentrations (P < 0.05) in the three major alkanes (C23, C31 and C33) in the Gramineae family than the freeze-dry method. Therefore, studies dealing with alkane concentrations should use the same drying method for all samples. Key words: Alkane pattern, steppe grassland, oven-dry, freeze-dry
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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 | 0.001 |
| 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) | 0.000 | 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 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".