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Record W2580802042 · doi:10.20381/ruor-11919

Combined nitrogen retention in an agricultural river system

2006· article· en· W2580802042 on OpenAlexaboutno aff
Christopher Allaway

Bibliographic record

VenueuO Research (University of Ottawa) · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureEnvironmental scienceNitrogenAgricultural economicsGeographyEconomicsChemistryArchaeology

Abstract

fetched live from OpenAlex

Since combined nitrogen is a pollutant in streams, rivers and coastal areas, conditions that favour nitrogen removal were identified. The importance of stream depth as a predictor of a reach's capacity to remove nitrogen was tested in the South Nation watershed (3915 km2), an agricultural watershed in eastern Ontario. Combined nitrogen (N) retention was estimated in 48 reaches across the watershed which varied in discharge (0.0008--118 m3 s-1), length (350 m to 5.2 km) and size from headwaters to the outflow of the South Nation River at the Ottawa River. Retention dynamics were also investigated within a few sites over the summer season. Retention efficiency (expressed as a percentage of inputs) varied widely for nitrate from almost complete removal within a reach to reaches acting as a net source. A narrower range in percent retention and loading was observed for total nitrogen (TN) among the sites suggesting that some forms of combined nitrogen are relatively inert. (Abstract shortened by UMI.)

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.200
Threshold uncertainty score0.397

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.223
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2006
Admission routes1
Has abstractyes

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