MétaCan
Menu
← Back to cohort
Record W4256380763 · doi:10.5194/bg-2017-337

The distribution of methylated sulfur compounds, DMS and DMSP, in Canadian Subarctic and Arctic marine waters during summer, 2015

2017· preprint· en· W4256380763 on OpenAlexfundaboutno aff
Tereza Jarníková, John W. H. Dacey, Martine Lizotte, Maurice Levasseur, Philippe D. Tortell

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDimethylsulfoniopropionateOceanographyArcticChlorophyll aSubarctic climateBayPhytoplanktonTransectSeawaterEnvironmental scienceDimethyl sulfideEnvironmental chemistryChemistrySulfurGeologyNutrient

Abstract

fetched live from OpenAlex

Abstract. We present seawater concentrations of dimethylsulfide (DMS), and dimethylsulfoniopropionate (DMSP) measured across a transect from the Labrador Sea to the Canadian Arctic Archipelago, during summer 2015. Using an automated ship-board gas chromatography system, and a membrane-inlet mass spectrometer, we measured a range of DMS (~ 1 nM to 18 nM) and DMSP concentrations (~ 1 nM to 150 nM) that was consistent with previous observations in the Arctic Ocean. The highest DMS and DMSP concentrations occurred in a localized region of Baffin Bay, where surface waters were characterized by high chlorophyll a (chl a) fluorescence, indicative of elevated phytoplankton biomass. Across the full sampling transect, there were only weak relationships between DMS/P, chl a fluorescence and other measured variables, including positive relationships between DMSP : chl a ratios and several taxonomic marker pigments, and elevated DMS/P concentrations in partially ice-covered areas. Our high spatial resolution measurements allowed us to examine DMS variability over small scales (

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 score0.034
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
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 head0.013
GPT teacher head0.224
Teacher spread0.211 · 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
Published2017
Admission routes2
Has abstractyes

Explore more

Same topicAtmospheric chemistry and aerosols→French-language works237,207→