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Record W2333199223 · doi:10.1021/es104116a

Isotopic Character of Nitrous Oxide Emitted from Streams

2011· article· en· W2333199223 on OpenAlexaff
Helen M. Baulch, Sherry L. Schiff, Simon J. Thuss, Peter Dillon

Bibliographic record

VenueEnvironmental Science & Technology · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsUniversity of WaterlooTrent University
Fundersnot available
KeywordsSTREAMSNitrous oxideTroposphereNitrateEnvironmental scienceEnvironmental chemistryGreenhouse gasAtmospheric sciencesChemistryHydrology (agriculture)GeologyOceanography

Abstract

fetched live from OpenAlex

Global models have indicated agriculturally impacted rivers and streams may be important sources of the greenhouse gas nitrous oxide (N(2)O). However, there is significant uncertainty in N(2)O budgets. Isotopic characterization can be used to help constrain N(2)O budgets. We present the first published measurements of the isotopic character of N(2)O emitted from low (2-4) order streams. Isotopic character of N(2)O varied seasonally, among streams, and over diel periods. On an annual basis, δ(18)O of emitted N(2)O (+47.4 to +51.4‰; relative to VSMOW) was higher than previously reported for larger rivers, but δ(15)N of emitted N(2)O (-16.2 to +2.4‰ among streams; relative to atmospheric N(2)) was similar to that of past studies. On an annual basis, all streams emitted N(2)O with lower δ(15)N than tropospheric N(2)O. Given these streams have elevated nitrate concentrations which are associated with enhanced N(2)O fluxes, this supports the hypothesis that streams are contributing to the accumulation of (15)N-depleted N(2)O in the troposphere.

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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.007
GPT teacher head0.160
Teacher spread0.152 · 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

Citations17
Published2011
Admission routes1
Has abstractyes

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