MétaCan
Menu
Back to cohort
Record W4389951305 · doi:10.5194/gchron-5-451-2023

The marine reservoir age of Greenland coastal waters

2023· article· en· W4389951305 on OpenAlexaboutno aff
Christof Pearce, Karen Søby Özdemir, Ronja Forchhammer Mathiasen, Henrieka Detlef, Jesper Olsen

Bibliographic record

VenueGeochronology · 2023
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsnot available
FundersDanmarks Frie Forskningsfond
KeywordsOceanographyGeologyPhysical geographyEnvironmental scienceGeography

Abstract

fetched live from OpenAlex

Abstract. Knowledge of the marine reservoir age is fundamental for creating reliable chronologies of marine sediment archives based on radiocarbon dating. This age difference between the 14C age of a marine sample and that of its contemporaneous atmosphere is dependent on several factors (among others, ocean circulation, water mass distribution, terrestrial runoff, upwelling, and sea-ice cover) and is therefore spatially heterogeneous. Anthropogenic influence on the global isotopic carbon system, mostly through atmospheric nuclear tests, has complicated the determination of the regional reservoir age correction ΔR, which therefore can only be measured in historic samples of known age. In this study we expand on the few existing measurements of ΔR for the coastal waters around Greenland, by adding 92 new radiocarbon dates on mollusks from museum collections. All studied mollusk samples were collected during historic expeditions of the late 19th and early 20th centuries, and besides coastal sites around Greenland, the new measurements also include localities from the western Labrador Sea, Baffin Bay, and the Iceland Sea. Together with existing measurements, the new results are used to calculate average ΔR values for different regions around Greenland, all in relation to Marine20, the most recent marine radiocarbon calibration curve. To support further discussions and comparison with previous datasets, we use the term ΔR13, where the suffix 13 refers to the previous calibration curve Marine13. Our study explores the links between the marine reservoir age and oceanography, sea-ice cover, water depth, mollusk feeding habits, and the presence of carbonate bedrock. Although we provide regional averages, we encourage people to consult the full catalogue of measurements and determine a suitable ΔR for each case individually, based on the exact location including water depth. Despite this significant expansion of the regional reservoir age database around Greenland, data from the northern coast, directly bordering the Arctic Ocean, remain missing.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.012
GPT teacher head0.221
Teacher spread0.209 · 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

Citations21
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueGeochronologySame topicHydrocarbon exploration and reservoir analysisFrench-language works237,207