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Record W3099209871 · doi:10.1002/lol2.10174

Continental margin sediments underlying the <scp>NE</scp> Pacific oxygen minimum zone are a source of nitrous oxide to the water column

2020· article· en· W3099209871 on OpenAlexafffund
Brett D. Jameson, Peter Berg, Damian S. Grundle, Catherine Stevens, S. Kim Juniper

Bibliographic record

VenueLimnology and Oceanography Letters · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsOcean Networks Canada SocietyUniversity of Victoria
FundersDivision of Ocean SciencesMemorial University of NewfoundlandUniversity of Victoria
KeywordsContinental marginContinental shelfOxygen minimum zoneWater columnUpwellingTransectBottom waterOceanographySedimentGeologyNitrogenGeomorphologyChemistryPaleontology

Abstract

fetched live from OpenAlex

Abstract Continental margin sediments are important sites of marine nitrogen cycling and potential contributors to atmospheric N 2 O emissions. We employed trace‐level N 2 O microsensors to measure vertical N 2 O profiles at submillimeter resolutions in intact cores from outer continental margin sediments underlying the NE Pacific oxygen minimum zone. We used mathematical modeling to estimate depth‐dependent rates of N 2 O production and fluxes to the overlying water along a transect of diminishing bottom water oxygen concentrations. Net sediment efflux was observed at all sites on the outer continental margin, with a mean value of 524 nmol m −2 d −1 . N 2 O efflux increased with decreased oxygen penetration depth in sediments. Enhanced N 2 O production and efflux were obtained when outer continental shelf sediments were experimentally exposed to lower bottom‐water O 2 concentrations, to simulate upwelling conditions. Our results underline the need for further investigation of the drivers of N 2 O production in continental margin sediments, and the relative importance of these environments to the global N 2 O budget.

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 score0.161
Threshold uncertainty score0.369

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)0.0000.000

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 head0.012
GPT teacher head0.177
Teacher spread0.165 · 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

Citations19
Published2020
Admission routes2
Has abstractyes

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