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Record W6888468225 · doi:10.18739/a2pg1hq63

Sediment geochemical data from the Bering Shelf and Yukon Delta, Eastern Bering Sea, June 2023

2025· dataset· en· W6888468225 on OpenAlexaboutno aff

Bibliographic record

VenueCalifornia Digital Library · 2025
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSedimentSediment trapSeabedArcticContinental shelfTotal organic carbonGrain sizeSediment transport

Abstract

fetched live from OpenAlex

This dataset contains geochemical and grain size measurements of seabed and suspended sediment samples collected from the Bering Shelf and Yukon prodelta in June 2023. These samples were collected during the 6-12 June 2023 Arctic Chief Scientist Training Cruise, which was a short cruise on the R/V Sikuliaq during its transit from Seward, Alaska to Nome, Alaska. The cruise was sponsored by the University National Oceanographic Laboratory System (UNOLS) Arctic Icebreaker Coordinating Committee and the National Science Foundation. These data were generated as a pilot data set to understand the fate of terrestrial organic carbon in the Yukon River delta and adjacent Bering Sea. Seabed sediment was collected at three locations (MC04, MC06, and MC08) using a multicorer. One seabed sediment sample was collected using a van veen grab sampler. Suspended sediment samples were collected using a hand-deployed niskin bottle and transferred into a clean 10-liter cubitainer for transport and temporary storage. Suspended sediment was filtered on the ship within 24 hours of collection using a Geotech barrel filter with a 0.45 micron Polyethersulfone (PES) membrane filter. Multicores were extruded on deck and subsamples were transferred to sterile whirl-pak sample bags. All sediment samples were frozen and subsequently shipped back to the lab in coolers. Sediment samples were analyzed for grain size, bulk elemental composition via X-ray fluorescence (XRF), and organic carbon and nitrogen concentrations and isotopes via EA-IRMS (elemental analyzer-isotope ratio mass spectrometry). Grain size distributions were measured using a Malvern mastersizer laser diffraction particle size analyzer at the University of Colorado Boulder. Bulk elemental composition was measured on the Rigaku XRF in the Analytical Geochemistry Lab at the University of New Mexico. Total organic carbon (TOC), total nitrogen (TN), and carbon/nitrogen isotopes were measured at the Center for Stable Isotopes at the University of New Mexico. Prior to EA-IRMS analyses, sediment samples were acid-treated to remove inorganic carbon following the method of Galy et al., 2007. References Galy, V., Bouchez, J., & France‐Lanord, C. (2007). Determination of total organic carbon content and δ13C in carbonate‐rich detrital sediments. Geostandards and Geoanalytical research, 31(3), 199-207.

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)0.000
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 score0.042
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.198
Teacher spread0.186 · 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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueCalifornia Digital LibrarySame topicArctic and Antarctic ice dynamicsFrench-language works237,207