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Record W4308149819 · doi:10.1029/2022gl100446

Challenging Radiocarbon Chronostratigraphies in Central Arctic Ocean Sediment

2022· article· en· W4308149819 on OpenAlexafffund
Claude Hillaire‐Marcel, Anne de Vernal, Yu-Fen Rong, Philippe Roberge, Tengfei Song

Bibliographic record

VenueGeophysical Research Letters · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGeologyHoloceneOceanographyRadiocarbon datingSedimentArcticSedimentary rockGlacial periodWinnowingPaleontologyArchaeology

Abstract

fetched live from OpenAlex

Abstract Based on the analysis of fish otolith assemblages from surface sediments of the Lomonosov Ridge (Arctic Ocean), we demonstrate that the very low Holocene sedimentation rates and winnowing of fine sediments result in the mixing of the whole Holocene populations at the sediment surface. Specimens from the Marine Isotope Stage (MIS) 3 or older could even be recovered in the surface due to a sedimentary hiatus at some locations in the central Arctic during the last glacial maximum. Two examples illustrate that 14 C‐stratigraphies from planktic foraminifers in underlying cored sediments reflect the mixing between Holocene and MIS 3 or older populations, thus invalidating continuous age‐depth inferences based on 14 C ages. Hence, much caution is required when attempting to set paleoceanographic reconstructions based on 14 C chronologies in a low sediment accumulation rate environment such as the central Arctic Ocean. Already published paleoceanographic reconstructions from this area might thus require some revisions.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.125
Threshold uncertainty score0.248

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.028
GPT teacher head0.268
Teacher spread0.240 · 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

Citations14
Published2022
Admission routes2
Has abstractyes

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