Vegetation gradients in relation to temporal fluctuation of environmental factors in Bekanbeushi peatland, Hokkaido, Japan
Bibliographic record
Abstract
The relationship between vegetation gradients and temporal variation of groundwater table depth, groundwater pH and electrical conductivity was studied in Bekanbeushi peatland, northern Japan. These environmental factors were expressed using four statistical parameters: maximum, minimum, mean and standard deviation or coefficient of variation during the growing season. The bog–fen–swamp/marsh gradient was primarily explained by minimum, maximum and mean groundwater table depth and minimum pH. The separation between the bog and the fen by minimum pH was particularly clear. Minimum conductivity was secondarily important for explaining this vegetation gradient. The swamp–marsh gradient was explained by the standard deviation of groundwater table depth. Maximum pH and conductivity were not significant in explaining either of these gradients. This study suggests that parameters that are obtained from the consecutive measurement of environmental factors may have differing significance in explaining vegetation gradients in these peatlands, and values from a single sampling may miss important ecological information.
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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".