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Record W2897111448 · doi:10.1029/2018gb005948

Isotopic Constraints on Nitrogen Transformation Rates in the Deep Sedimentary Marine Biosphere

2018· article· en· W2897111448 on OpenAlexaff
Carolyn Buchwald, K. Homola, Arthur J. Spivack, Emily R. Estes, Richard W. Murray, Scott D. Wankel

Bibliographic record

VenueGlobal Biogeochemical Cycles · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsDalhousie University
FundersNational Science Foundation
KeywordsAnoxic watersNitrateIsotopes of nitrogenNitriteDenitrificationEnvironmental chemistryNitrogen cycleNitrogenCyclingStable isotope ratioSedimentary rockChemistryOceanographyEnvironmental scienceGeologyGeochemistry

Abstract

fetched live from OpenAlex

Abstract Little is known about the nature of microbial community activity contributing to the cycling of nitrogen in organic‐poor sediments underlying the expansive oligotrophic ocean gyres. Here we use pore water concentrations and stable N and O isotope measurements of nitrate and nitrite to constrain rates of nitrogen cycling processes over a 34‐m profile from the deep North Atlantic spanning fully oxic to anoxic conditions. Using a 1‐D reaction‐diffusion model to predict the distribution of nitrogen cycling rates, results converge on two distinct scenarios: (1) an exceptionally high degree of coupling between nitrite oxidation and nitrate reduction near the top of the anoxic zone or (2) an unusually large N isotope effect (~60‰) for nitrate reduction that is decoupled from the corresponding O isotope effect, which is possibly explained by enzyme‐level interconversion between nitrite and nitrate.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.008
GPT teacher head0.215
Teacher spread0.207 · 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.

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

Citations20
Published2018
Admission routes1
Has abstractyes

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