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Record W2807952008 · doi:10.5194/bg-15-5891-2018

An intercomparison of oceanic methane and nitrous oxide measurements

2018· article· en· W2807952008 on OpenAlexaff
Samuel T. Wilson, Hermann W. Bange, Damian L. Arévalo‐Martínez, Jonathan Barnes, Alberto Borges, Ian Brown, John L. Bullister, Macarena Burgos, David Capelle, Michael Casso, Mercedes de la Paz, Laura Farı́as, Lindsay Fenwick, Sara Ferrón, Gerardo Azócar García, Michael Glockzin, David M. Karl, Annette Kock, Sarah M. Laperriere, Cliff S. Law, Cara C. Manning, Andrew Marriner, Jukka‐Pekka Myllykangas, J. Pohlman, Andrew P. Rees, Alyson E. Santoro, Philippe D. Tortell, Robert C. Upstill‐Goddard, David P. Wisegarver, Guiling Zhang, Gregor Rehder

Bibliographic record

VenueBiogeosciences · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of British Columbia
FundersNational Research Foundation of KoreaNatural Environment Research CouncilSight Research UKGordon and Betty Moore FoundationSimons Foundation
KeywordsNitrous oxideMethaneTrace gasSeawaterEnvironmental scienceEnvironmental chemistryWater columnBiogeochemical cycleChemistryAtmosphere (unit)OceanographyMeteorologyGeology

Abstract

fetched live from OpenAlex

Abstract. Large-scale climatic forcing is impacting oceanic biogeochemical cycles and is expected to influence the water-column distribution of trace gases, including methane and nitrous oxide. Our ability as a scientific community to evaluate changes in the water-column inventories of methane and nitrous oxide depends largely on our capacity to obtain robust and accurate concentration measurements that can be validated across different laboratory groups. This study represents the first formal international intercomparison of oceanic methane and nitrous oxide measurements whereby participating laboratories received batches of seawater samples from the subtropical Pacific Ocean and the Baltic Sea. Additionally, compressed gas standards from the same calibration scale were distributed to the majority of participating laboratories to improve the analytical accuracy of the gas measurements. The computations used by each laboratory to derive the dissolved gas concentrations were also evaluated for inconsistencies (e.g., pressure and temperature corrections, solubility constants). The results from the intercomparison and intercalibration provided invaluable insights into methane and nitrous oxide measurements. It was observed that analyses of seawater samples with the lowest concentrations of methane and nitrous oxide had the lowest precisions. In comparison, while the analytical precision for samples with the highest concentrations of trace gases was better, the variability between the different laboratories was higher: 36 % for methane and 27 % for nitrous oxide. In addition, the comparison of different batches of seawater samples with methane and nitrous oxide concentrations that ranged over an order of magnitude revealed the ramifications of different calibration procedures for each trace gas. Finally, this study builds upon the intercomparison results to develop recommendations for improving oceanic methane and nitrous oxide measurements, with the aim of precluding future analytical discrepancies between laboratories.

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)0.009
metaresearch head score (Gemma)0.007
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 score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.022
GPT teacher head0.250
Teacher spread0.228 · 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

Citations82
Published2018
Admission routes1
Has abstractyes

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