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Record W4205661276 · doi:10.1080/15230430.2021.2000566

Ice-covered ponds in the Untersee Oasis (East Antarctica): Distribution, chemical composition, and trajectory under a warming climate

2021· article· en· W4205661276 on OpenAlexafffund
Benoit Faucher, Denis Lacelle, Nicole B. Marsh, David Fisher, Dale T. Andersen

Bibliographic record

VenueArctic Antarctic and Alpine Research · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsUniversity of Ottawa
FundersPolar Knowledge CanadaTawani Foundation
KeywordsTrajectoryEnvironmental scienceDistribution (mathematics)ClimatologyGlobal warmingComposition (language)Physical geographyGeographyClimate changeOceanographyGeology

Abstract

fetched live from OpenAlex

Climate change is impacting lakes and ponds in Antarctica. To that end, we investigated the distribution and chemical composition of ice-covered ponds in Untersee Oasis, East Antarctica. Thirty-nine ponds were inventoried, and the thirteen sampled ponds have low total dissolved solutes (TDS) with a Ca(Na)-SO4 or Na-Cl geochemical facies. Tritium and radiocarbon measurements of the total inorganic carbon (TIC) suggest that the ponds are recharged by modern snowmelt. Hierarchical cluster analysis grouped the ponds based on the amount of potential incoming solar radiation reaching their surface. Ponds receiving higher insolation develop moats or completely lose their ice cover during summer, have lower pH, and higher TDS, δ18O, total inorganic carbon, and δ13CTIC,which suggest CO2 availability is not limiting benthic photosynthetic activity. The ponds that receive lower insolation retain their full ice cover and remain well-sealed to direct exchanges with the atmosphere, have high pH, and lower TDS and TIC, and likely host a CO2-starved benthic microbial ecosystem. Therefore, the state of the ponds’ ice cover evolved their hydrochemistry along different trajectories. The findings can be used to predict the trajectory of the chemical composition of the ponds and effect on biological productivity as the phenology of their ice cover shifts under a warming climate.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.030
GPT teacher head0.306
Teacher spread0.276 · 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 teacher head, not a consensus.

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

Citations4
Published2021
Admission routes2
Has abstractyes

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