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Record W7099444991

Reconstructing Organic Carbon Accumulation and

2015· article· en· W7099444991 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicGerman Social Sciences and History
Canadian institutionsnot available
Fundersnot available
KeywordsOrganic matterTotal organic carbonSedimentary organic matterSedimentClimate changeGreenhouse gasCarbon cycleBorealGlobal warming
DOInot available

Abstract

fetched live from OpenAlex

Over the past century, the global climate system has experienced unprecedented warming due to the rapid increase of greenhouse gas concentrations. Thus, understanding the fate of CO2 once it is released is critical to evaluating the impacts of future climate change. Lake sediments have the potential to store large quantities of CO2 in the form of organic carbon, yet the factors which control organic carbon burial efficiency in lakes are not fully understood. Consequently, this project examines the sedimentary record from one lake spanning the boreal forest-tundra ecotone in the eastern Mealy Mountains of southeastern Labrador, Canada in order to identify lake and watershed controls on organic carbon accumulation and evaluate the sensitivity of organic matter accumulation to changing climatic conditions. The pronounced environmental gradient and significant post-glacial environmental changes in this region provide an ideal setting for testing controls on organic matter accumulation. This study presents results of a multi-proxy reconstruction of one sediment record recovered from a lake located in the Mealy Mountains (53°N, 58°W). Proxies used in this study included % organics (%LOI, %C, and %N), XRF elemental analysis, magnetic susceptibility, and fossil pigment

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.499
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.117
GPT teacher head0.348
Teacher spread0.231 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2015
Admission routes1
Has abstractyes

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