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Record W2903896275 · doi:10.1029/2018gb005985

Insights From the<sup>238</sup>U‐<sup>234</sup>Th Method Into the Coupling of Biological Export and the Cycling of Cadmium, Cobalt, and Manganese in the Southeast Pacific Ocean

2018· article· en· W2903896275 on OpenAlexaff
Erin Black, Phoebe J. Lam, Jong‐Mi Lee, Ken O. Buesseler

Bibliographic record

VenueGlobal Biogeochemical Cycles · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsDalhousie University
FundersNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsGeotracesParticulatesManganeseCadmiumBiogeochemical cycleSediment trapEnvironmental scienceEnvironmental chemistryCobaltFlux (metallurgy)PhosphorusCyclingOceanographySeawaterChemistryGeologyTotal organic carbonInorganic chemistry

Abstract

fetched live from OpenAlex

Abstract Better constraints on the magnitude of particulate export and the residence times of trace elements are required to understand marine food web dynamics, track the transport of anthropogenic trace metals in the ocean, and improve global climate models. While prior studies have been successful in constructing basin‐scale budgets of elements like carbon in the upper ocean, the cycling of particulate trace metals is poorly understood. The 238 U‐ 234 Th method is used here with data from the GP‐16 GEOTRACES transect to investigate the upper ocean processes controlling the particulate export of cadmium, cobalt, and manganese in the southeastern Pacific. Patterns in the flux data indicated that particulate cadmium and cobalt behave similarly to particulate phosphorus and organic carbon, with the highest export in the productive coastal region and decreasing flux with depth due to remineralization. The export of manganese was influenced by redox conditions at the low oxygen coastal stations and by precipitation and/or scavenging elsewhere. Residence times with respect to export (total inventory divided by particulate flux) for phosphorus, cadmium, cobalt, and manganese in the upper 100 and 200 m were determined to be on the order of months to years. These GEOTRACES‐based synthesis efforts, combining a host of concentration and tracer data with unprecedented resolution, will help to close the oceanic budgets of trace metals.

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 score0.543
Threshold uncertainty score0.985

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 science0.0010.000
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 head0.014
GPT teacher head0.232
Teacher spread0.218 · 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

Citations27
Published2018
Admission routes1
Has abstractyes

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