Holocene peatland palaeoclimate archives and aeolian dust deposition
Bibliographic record
Abstract
The reconstruction of past water table levels in ombrotrophic peatlands is a long-established method for studying past regional hydroclimatic conditions. Peat strata are typically investigated for biological (e.g. plant macrofossils, testate amoebae, pollen) and geochemical (e.g. peat decomposition products and water isotopes) evidence to reconstruct bog surface wetness (BSW) at individual sites or to reconstruct the isotopic qualities of the precipitation that mire plant species used to synthesise plant tissues. Integration of BSW records across regions is then used to understand the temporal and spatial patterns of regional hydroclimatic variability. However, in recent years there has been increasing recognition that internal processes in the peatlands themselves and allogenic factors, such as mineral dust deposition and other forms of aerial pollution, could confound attempts to produce a clear picture of past hydroclimatic variability from peatlands. This study explores the impact of wind-blown mineral deposition on bog functioning in both high deposition environments (Japan and UK) and in a low deposition region (Northern Newfoundland) to understand how these inputs might impact possible climate signals preserved in raised peat strata. The examination of this ‘dust gradient’ shows that there may be multiple climate-driven signals in peat and that the contribution of long distance aeolian transport can be discerned when local inputs are minimal.
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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 | 0.002 | 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) | 0.002 | 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".