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Record W2057635856 · doi:10.1029/2007jg000442

Biogeochemical evolution of cryoconite holes on Canada Glacier, Taylor Valley, Antarctica

2007· article· en· W2057635856 on OpenAlexaboutno aff
Elizabeth Bagshaw, Martyn Tranter, Andrew G. Fountain, Kathleen A. Welch, Hassan Basagic, W. Berry Lyons

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsnot available
FundersNatural Environment Research CouncilNational Science Foundation
KeywordsBiogeochemical cycleGlacierGeologyEcosystemOceanographyAtmospheric sciencesEnvironmental chemistryGeomorphologyEcologyChemistry

Abstract

fetched live from OpenAlex

The cryoconite holes of the McMurdo Dry Valleys are simple, closed biogeochemical systems involving water, ice, mineral and organic debris, which serve as ecosystems for consortia of microorganisms. This study is the first to document the seasonal and annual chemical evolution of solutes in cryoconite holes. Samples of glacier ice, frozen cryoconite holes and those containing water were collected during the austral summer of 2005–2006. The isolation age was calculated from the excess Cl − in the holes, and varied from 0 to 5 years (a), consistent with the last hot summer when the cryoconite holes were open to the atmosphere. The holes progressively deepen with isolation age. Variations in DIC, DOC, K + and SO 4 2− suggest that dissolution of primary minerals in the cryoconite debris, cyclical precipitation and dissolution of secondary carbonates, net photosynthesis over summer and net respiration during the autumnal freeze are the principal reactions which perturb the seasonal and annual solute concentrations in the holes. DOC is generated in the holes at a rate of 7.5 μ g C cm −2 a −1 , and non‐sea‐salt K + accumulates in frozen holes at a rate of 0.073 μ eq cm −2 a −1 . We infer that C cycling is complex even in these otherwise simple systems.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.527
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.018
GPT teacher head0.297
Teacher spread0.280 · 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

Citations165
Published2007
Admission routes1
Has abstractyes

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