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Record W6944419766 · doi:10.18739/a2cc0tv8c

Stable isotopes of carbon (δ13C-DIC) and oxygen (δ18O-H2O) in the western Arctic Ocean (2021)

2023· dataset· en· W6944419766 on OpenAlexaboutno aff

Bibliographic record

VenueUC Santa Barbara · 2023
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsArcticBiogeochemical cycleStable isotope ratioCarbon fibersHydrographyIsotopes of carbonThe arcticCarbon cycle

Abstract

fetched live from OpenAlex

Stable isotopes of carbon (δ13C-DIC) and oxygen (δ18O-H2O) are two essential tracers that help understand the changing Arctic water masses and carbon cycles. However, the interplay of physical, chemical, and biological factors and their influence on δ13C-DIC in the Arctic Ocean are poorly understood. Therefore, we investigated the distributions of δ13C-DIC and δ18O-H2O in the western Arctic Ocean during the Mirai 2021 cruise from September 12th to October 2nd under the framework of the Arctic Challenge for Sustainability II Project (ArCS II). Here we present the dataset of δ13C-DIC and δ18O-H2O, which covers the central and eastern Chukchi Sea, extending from the Bering Strait to the southwestern Canada Basin. Combined with other hydrographic and biogeochemical parameters, δ18O-H2O samples could be used to decipher and quantify the contributions of source water masses in each sample. δ13C-DIC samples could be helpful to better understand the carbon export pathways and partition of potential carbon sources. The observations of δ18O-H2O and δ13C-DIC facilitate a better understanding of the carbon flows, exports, and degradation from highly productive shelves to oligotrophic basins, and thus a better prediction of future changes in the Arctic carbon dynamics.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.053
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.003

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 head0.021
GPT teacher head0.265
Teacher spread0.244 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2023
Admission routes1
Has abstractyes

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