MétaCan
Menu
Back to cohort
Record W1800977649 · doi:10.1029/2011gl050355

Net carbon accumulation of a high‐latitude permafrost palsa mire similar to permafrost‐free peatlands

2012· article· en· W1800977649 on OpenAlexafffund
David Olefeldt, Nigel T. Roulet, Onil Bergeron, Patrick Crill, K. Bäckstrand, Torben R. Christensen

Bibliographic record

VenueGeophysical Research Letters · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsSte. Anne's HospitalUniversity of GuelphMcGill University
FundersVetenskapsrådetSweden-America FoundationCanadian Foundation for Climate and Atmospheric Sciences
KeywordsPermafrostSubarctic climateMirePeatEnvironmental scienceClimate changeBorealEcosystemPhysical geographyGeologyEcologyOceanographyGeography

Abstract

fetched live from OpenAlex

Palsa mires, nutrient poor permafrost peatlands common in subarctic regions, store a significant amount of carbon (C) and it has been hypothesized their net ecosystem C balance (NECB) is sensitive to climate change. Over two years we measured the NECB for Stordalen palsa mire and found it to accumulate 46 g C m −2 yr −1 . While Stordalen NECB is comparable to nutrient poor peatlands without permafrost, the component fluxes differ considerably in magnitude. Specifically, Stordalen had both lower growing season CO 2 uptake and wintertime CO 2 losses, but importantly also low dissolved organic carbon exports and hydrocarbon (mainly methane) emissions. Restricted C losses from palsa mires are likely to have facilitated C accumulation of unproductive subarctic permafrost peatlands. Continued climate change and permafrost thaw is likely to amplify several component fluxes, with an uncertain overall effect on NECB – highlighting the necessity for projections of high‐latitude C storage to consider all C fluxes.

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)0.001
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 score0.086
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.117
GPT teacher head0.350
Teacher spread0.233 · 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

Citations120
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueGeophysical Research LettersSame topicClimate change and permafrostFrench-language works237,207