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Record W2025938446 · doi:10.1029/2012eo030009

Peatlands as a model ecosystem of soil carbon dynamics: Reply to Comment on “Peatlands and their role in the global carbon cycle”

2012· article· en· W2025938446 on OpenAlexaff
Zicheng Yu, David W. Beilman, Steve Frolking, Glen M. MacDonald, Nigel T. Roulet, Philip Camill, Dan J. Charman

Bibliographic record

VenueEos · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsMcGill University
Fundersnot available
KeywordsLagrangianPeatAtmosphere (unit)TrajectoryCarbon cycleEcosystemFace (sociological concept)Environmental scienceEarth scienceMeteorologyEcologyGeographyGeologyPhysicsArchaeologySocial scienceSociologyBiology

Abstract

fetched live from OpenAlex

AGU Chapman Conference on Advances in Lagrangian Modeling of the Atmosphere; Grindelwald, Switzerland, 10–14 October 2011 Under the majestic gaze of the Eiger north face in Switzerland, an international group of researchers met as part of a Chapman Conference to discuss advances in Lagrangian modeling of the atmosphere. Lagrangian models track the movement of air parcels, giving rise to trajectory information and source/receptor linkages that have become increasingly popular as tools used by geoscientists. The conference was an opportunity for a diverse group of researchers developing and applying Lagrangian models to congregate and discuss the use of such models to understand geophysical phenomena and to identify how to further improve the models. The 98 participants (of which 17 were graduate students) hailed from 19 countries around the world.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.661
Threshold uncertainty score0.664

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 head0.006
GPT teacher head0.215
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

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 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
Published2012
Admission routes1
Has abstractyes

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