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Record W1978040704 · doi:10.1191/095968300671749538

Carbon accumulation in permafrost peatlands in the Northwest Territories and Nunavut, Canada

2000· article· en· W1978040704 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Holocene · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPeatSubarctic climateBorealPermafrostArcticPhysical geographyCarbon fibersBogEnvironmental scienceIce coreGeologyTundraAtmospheric sciencesClimatologyOceanographyGeographyArchaeologyPaleontology

Abstract

fetched live from OpenAlex

Average long-term apparent rates of carbon (C) accumulation (LARCA) were estimated for four peat cores from Arctic and Subarctic Canada. Detailed analyses of dry bulk-density and C content were used to determine variations in C accumulation rates throughout the cores. LARCA range from 12.5 to 16.5 g C m -2 yr -1 over the past 6700-10000 years. Rates are lower for the surface layers of Arctic high-centred peat polygons, at 5.3 to 7.1 g C m -2 yr -1 for the last 3500-4500 years. By comparison, the rate for the near-surface peat from a Sphagnum fuscum hummock in the high Subarctic was considerably higher, at 24.1 g C m -2 yr -1 . The highest carbon accumulation rates were from core segments older than 4500 BP, which represent fen stages according to palaeoecological analysis. The average LARCA in our study are considerably lower than recent estimates of average carbon accumulation in Boreal peatlands. This difference is attributable partly to lower carbon percentages in our cores compared to the mean or estimated values of 50 to 51.7% used in those studies. Another factor is the presence of ground ice, which exaggerates the apparent peat depth and leads to erroneously high values if cumulative carbon estimates are based on depth. Using cumulative dry bulk-density, as we have done, eliminates the influence of ground ice and thus makes more accurate estimates possible.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.214

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.219
Teacher spread0.209 · 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