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Record W6945825511 · doi:10.26022/ieda/112229

Sr-Nd-Pb isotope ratios in snow pits from Denali National Park and sediments from southcentral Alaska

2022· dataset· en· W6945825511 on OpenAlexaboutno aff

Bibliographic record

VenueEarthChem Library · 2022
Typedataset
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsnot available
Fundersnot available
KeywordsNational parkTransectSnowLoessGlacierHydrology (agriculture)MoraineDeposition (geology)Range (aeronautics)

Abstract

fetched live from OpenAlex

We measured Sr-Nd-Pb isotope ratios of impurities filtered from an elevational transect of surface snow pits (2180–5240 m a.s.l) sampled in June 2016 in the Alaska Range of Denali National Park, Alaska to investigate the sources of dust and pollution aerosols. Comparable measurements on 20 fine-grained glaciofluvial silt and loess samples from southcentral Alaska and the Kluane Lake region of Yukon, Canada, were developed to characterize the local glaciogenic dust source composition. The dataset includes 87Sr/86Sr, 143Nd/144Nd, epsilon Nd, 206Pb/204Pb, 207Pb/204Pb, 208Pb/204Pb, 206Pb/207Pb, and 208Pb/207Pb ratios.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.110
Threshold uncertainty score0.219

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.005

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 head0.042
GPT teacher head0.288
Teacher spread0.246 · 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 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

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