MétaCan
Menu
Back to cohort
Record W2986641007 · doi:10.1038/s41467-019-13111-7

Isotopic composition of oceanic dissolved black carbon reveals non-riverine source

2019· article· en· W2986641007 on OpenAlexaff
Sasha Wagner, Jay A. Brandes, Robert G. M. Spencer, Kun Ma, Sarah Z. Rosengard, José Mauro Sousa de Moura, Aron Stubbins

Bibliographic record

VenueNature Communications · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of British Columbia
FundersNational Science Foundation
KeywordsdBcEnvironmental scienceCarbon fibersIsotopes of carbonCarbon blackIsotopic signatureCharcoalEnvironmental chemistryOceanographyEarth scienceGeologyStable isotope ratioChemistryTotal organic carbonMaterials science

Abstract

fetched live from OpenAlex

Abstract A portion of the charcoal and soot produced during combustion processes on land (e.g., wildfire, burning of fossil fuels) enters aquatic systems as dissolved black carbon (DBC). In terms of mass flux, rivers are the main identified source of DBC to the oceans. Since DBC is believed to be representative of the refractory carbon pool, constraining sources of marine DBC is key to understanding the long-term persistence of carbon in our global oceans. Here, we use compound-specific stable carbon isotopes (δ13C) to reveal that DBC in the oceans is ~6‰ enriched in 13C compared to DBC exported by major rivers. This isotopic discrepancy indicates most riverine DBC is sequestered and/or rapidly degraded before it reaches the open ocean. Thus, we suggest that oceanic DBC does not predominantly originate from rivers and instead may be derived from another source with an isotopic signature similar to that of marine phytoplankton.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.229
Teacher spread0.221 · 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

Citations131
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueNature CommunicationsSame topicAtmospheric chemistry and aerosolsFrench-language works237,207