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Record W4394118758 · doi:10.6084/m9.figshare.23699255

Yukon ice patches: Bryophyte generation from ancient ice-entombed assemblages

2023· dataset· en· W4394118758 on OpenAlexaboutno aff
Brittney L. Miller, Catherine La Farge

Bibliographic record

VenueFigshare · 2023
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicBryophyte Studies and Records
Canadian institutionsnot available
Fundersnot available
KeywordsBryophyteArchaeologyGeologyGeographyPhysical geographyPaleontologyOceanographyEcologyBiology

Abstract

fetched live from OpenAlex

In Southwestern Yukon, ice patches have shown substantial retreat since the Little Ice Age (1600–1900 AD) in response to warming trends. These ice patches support unique alpine wetlands that have formed habitats for diverse flora and fauna over millennia. With ice retreat, pristine bryophyte populations are exposed beneath accumulated ancient dung. Given that bryophytes have been shown to survive extreme conditions including ice entombment and can regenerate from viable cells, emergent ice margin bryophyte and dung samples from the Granger and Gladstone ice patches were assayed for regrowth potential under growth chamber conditions. Diaspore (spore/fragment) generation of species found in the original subfossil material was indicated in 68 percent of assays, emphasizing the cyclical establishment of ancient ice patch vegetation. One of the oldest samples, dating 4036 calibrated years BP from the Gladstone ice patch margin, showed remarkable bryophyte generation from diaspores in dung. These Yukon ice patches form reservoirs of cryopreserved biota and have a critical role in maintaining alpine diversity, which provides summer refuge for caribou and other alpine fauna. Ice margin fluctuations, which bury and release populations through time, are part of a complex revegetation sequence in alpine regions that has followed deglaciation.

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 categoriesInsufficient 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 score0.029
Threshold uncertainty score0.984

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0460.017

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 head0.070
GPT teacher head0.259
Teacher spread0.189 · 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
Published2023
Admission routes1
Has abstractyes

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