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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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0030.008
Open science0.0060.003
Research integrity0.0320.041
Insufficient payload (model declined to judge)0.0070.005

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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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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