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Record W3095189401 · doi:10.1002/hyp.13955

A <scp>50‐year</scp> record of nitrate concentrations in the Slapton Ley Catchment, Devon, United Kingdom

2020· article· en· W3095189401 on OpenAlexaff
Tim Burt, Fred Worrall, Nicholas Howden, Helen P. Jarvie, Andrew Pratt

Bibliographic record

VenueHydrological Processes · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsUniversity of Waterloo
FundersDurham University
KeywordsEutrophicationNitrateSTREAMSEnvironmental scienceHydrology (agriculture)Water qualitySedimentNutrientDrainage basinGeographyEcology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score0.348

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.040
GPT teacher head0.244
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2020
Admission routes1
Has abstractyes

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