A <scp>50‐year</scp> record of nitrate concentrations in the Slapton Ley Catchment, Devon, United Kingdom
Bibliographic record
Abstract
Abstract Slapton Ley, a coastal lake, is the largest natural body of fresh water in south‐west England. There was concern in the 1960s that the lake was becoming increasingly eutrophic. To quantify inputs of water, sediment and nutrients into the lake, Slapton Ley Field Centre initiated a programme of weekly water quality sampling in September 1970. Of all the chemical properties which have been measured over the decades, the nitrate record has been the subject of more research than any other. The weekly monitoring has been supplemented by research projects aimed at understanding aspects of processes and patterns of nitrate delivery to the stream network. Three aspects of the nitrate record are reviewed: short‐term process dynamics; the annual cycle of influent streams and the lake itself; and long‐term trends. In the first two decades of monitoring, there was increasing concern about a trend of rising nitrate concentrations, an issue in most lowland rivers in the United Kingdom at the time. In the 1990s, nitrate concentrations levelled off and then have fallen steadily in recent years. In relation to eutrophication, there are clear signs of improvement in the influent streams, but concerns remain about water quality in the lake itself.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".