Hydroecological Responses to Climate Change in Northern Catchments
Bibliographic record
Abstract
Northern Watershed Ecosystem Response to Climate Change (North‐Watch) Workshop III: Hydroecological Responses to Climate Change in Northern Catchments; Aviemore, United Kingdom, 29 August to 2 September 2010; North‐Watch is an interdisciplinary intersite comparison project funded by the Leverhulme Trust, United Kingdom, and run by the Northern Rivers Institute, University of Aberdeen, Aberdeen, United Kingdom. The overall aim of the North‐Watch project is to facilitate an intercatchment comparison study of high‐latitude catchments that will yield a comprehensive, interdisciplinary, and regional understanding of the recent effects of climatic change and provide a stronger scientific basis for predicting what further changes are likely. Examining a range of sites across a climatic transect in the northern zone will give a much stronger regional perspective on the responses to climatic change than individual studies alone. The project is analyzing long‐term data from experimental catchments including sensitive boreal, sub‐Arctic, and sub‐Alpine environments ranging from the Yukon and northern Sweden to the Scottish Cairngorms to assess the integrated physical, chemical, and biological response to climatic change.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".