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Record W2592261212 · doi:10.1002/2016jc012465

Concentrations and cycling of DMS, DMSP, and DMSO in coastal and offshore waters of the Subarctic Pacific during summer, 2010‐2011

2017· article· en· W2592261212 on OpenAlexafffund
Elizabeth Asher, John W. H. Dacey, Debby Ianson, M. Angélica Peña, Philippe D. Tortell

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsFisheries and Oceans CanadaUniversity of British Columbia
FundersFisheries and Oceans CanadaDivision of Ocean SciencesNatural Sciences and Engineering Research Council of CanadaUniversity of British Columbia
KeywordsDimethylsulfoniopropionateUpwellingSubarctic climateOceanographyHydrographyDimethyl sulfideChlorophyll aEnvironmental sciencePolar nightBiogeochemical cycleEnvironmental chemistrySulfurPhytoplanktonChemistryGeologyArcticNutrient

Abstract

fetched live from OpenAlex

Abstract Concentrations of dimethylsulfide (DMS), measured in the Subarctic Pacific during summer 2010 and 2011, ranged from ∼1 to 40 nM, while dissolved dimethylsulfoxide (DMSO) concentrations (range 13‐23 nM) exceeded those of dissolved dimethyl sulfoniopropionate (DMSP) (range 1.3–8.8 nM). Particulate DMSP dominated the reduced sulfur pool, reaching maximum concentrations of 100 nM. Coastal and off shore waters exhibited similar overall DMS concentration ranges, but sea‐air DMS fluxes were lower in the oceanic waters due to lower wind speeds. Surface DMS concentrations showed statistically significant correlations with various hydrographic variables including the upwelling intensity (r 2 = 0.52, p < 0.001) and the Chlorophyll a /mixed layer depth ratio (r 2 = 0.52, p < 0.001), but these relationships provided little predictive power at small scales. Stable isotope tracer experiments indicated that the DMSP cleavage pathway always exceeded the DMSO reduction pathway as a DMS source, leading to at least 85% more DMS production in each experiment. Gross DMS production rates were positively correlated with the upwelling intensity, while net rates of DMS production were significantly correlated to surface water DMS concentrations. This latter result suggests that our measurements captured dominant processes driving surface DMS accumulation across a coastal‐oceanic gradient.

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)0.001
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 score0.012
Threshold uncertainty score0.337

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.037
GPT teacher head0.288
Teacher spread0.251 · 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

Citations44
Published2017
Admission routes2
Has abstractyes

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