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Record W2890232832 · doi:10.1038/s41558-018-0271-1

Latitudinal limits to the predicted increase of the peatland carbon sink with warming

2018· article· en· W2890232832 on OpenAlexaff
Angela Gallego‐Sala, Dan J. Charman, Simon Brewer, Susan Page, I. Colin Prentice, Pierre Friedlingstein, Steven Grahame Moreton, Matthew J. Amesbury, David W. Beilman, Svante Björck, Tatiana Blyakharchuk, Christopher Bochicchio, Robert K. Booth, Joan Bunbury, Philip Camill, Donna Carless, Rodney A. Chimner, Michael J. Clifford, Elizabeth L. Cressey, Colin J. Courtney Mustaphi, François De Vleeschouwer, Rixt de Jong, Barbara Fiałkiewicz-Kozieł, Sarah A. Finkelstein, Michelle Garneau, Esther Githumbi, John Hribjlan, James R. Holmquist, Paul Hughes, Chris Jones, Miriam C. Jones, Edgar Karofeld, Eric S. Klein, Ulla Kokfelt, Atte Korhola, Terri Lacourse, Gaël Le Roux, Mariusz Lamentowicz, David J. Large, Martin Lavoie, Julie Loisel, Helen Mackay, Glen M. MacDonald, M. Mäkilä, Gabriel Magnan, Rob Marchant, Katarzyna Marcisz, Antonio Martı́nez Cortizas, Charly Massa, Paul Mathijssen, Dmitri Mauquoy, Tim Mighall, Fraser Mitchell, Patrick Moss, J. E. Nichols, Pirita Oksanen, Lisa Orme, Maara Packalen, Stephen D. Robinson, Thomas P. Roland, Nicole K. Sanderson, A. Britta K. Sannel, Noemí Silva-Sánchez, Natascha Steinberg, Graeme T. Swindles, T. Edward Turner, Joanna Uglow, Minna Väliranta, Simon van Bellen, M. van der Linden, B. van Geel, Guoping Wang, Zicheng Yu, Joana Zaragoza‐Castells, Yan Zhao

Bibliographic record

VenueNature Climate Change · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsUniversité LavalUniversity of VictoriaMinistry of Natural Resources and ForestryUniversité du Québec à MontréalUniversity of Toronto
FundersNarodowym Centrum NaukiSight Research UKNatural Environment Research CouncilMet OfficeImperial College LondonDepartment for Environment, Food and Rural Affairs, UK Government
KeywordsPeatCarbon sinkSink (geography)Environmental scienceGlobal warmingClimate changeLatitudeGreenhouse gasAtmospheric sciencesGrowing seasonCarbon dioxideCarbon cycleCarbon fibersClimatologyEcologyEcosystemGeographyGeologyBiology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.238
Teacher spread0.224 · 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 designSimulation or modeling
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

Citations348
Published2018
Admission routes1
Has abstractno

Explore more

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