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Record W6907318389 · doi:10.18739/a2x05xf4c

Lake Qaupat, Baffin Island 5,800 Year Plant Wax and Geochemical Data

2022· dataset· en· W6907318389 on OpenAlexaboutno aff

Bibliographic record

VenueCalifornia Digital Library · 2022
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsWaxArcticPlant communityPrecipitationSeasonalityTerrestrial plantWater cycleClimate changeSpring (device)

Abstract

fetched live from OpenAlex

Paleo water isotope records can elucidate how the Arctic water cycle responded to past climate changes. We analyze the hydrogen isotope composition (δ2H) of plant‐derived n‐alkanoic acids (waxes) from Lake Qaupat, Baffin Island, Nunavut, Canada, to assess moisture sources and seasonality during the past 5.8 kiloannum (ka). We compare this record to a sedimentary ancient DNA (sedaDNA)‐inferred vascular plant record from the same lake, aiming to overcome the uncertainty of plant community impacts on leaf waxes. As the sedaDNA record reveals a stable plant community after the colonization of Betula sp. at 6.1 ka, we interpret plant wax δ2H values to reflect climate, specifically mean annual precipitation δ2H. However, the distributions of n‐alkanoic acid homologs suggest that aquatic mosses, which are not represented in the sedaDNA record, may become more abundant towards the present. Therefore, we cannot exclude the possibility that changes in the plant community cause changes in the plant wax δ2H record, particularly long‐chain waxes, which become less abundant through this record. We find that Lake Qaupat mid‐chain plant wax δ2H is enriched coincident with high Labrador Sea summer surface temperature, which suggests that local moisture sources in summer and early autumn have the greatest impact on precipitation isotopes in this region.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.319
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)0.3210.002

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 head0.206
Teacher spread0.178 · 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; both teacher heads agree on what is shown here.

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
Published2022
Admission routes1
Has abstractyes

Explore more

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