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Record W2968567220 · doi:10.1038/s41467-019-11394-4

Ice sheets matter for the global carbon cycle

2019· review· en· W2968567220 on OpenAlexaff
Jemma L. Wadham, Jon Hawkings, Lev Tarasov, Lauren Gregoire, Robert G. M. Spencer, Marcus Gutjahr, Andy Ridgwell, Karen E. Kohfeld

Bibliographic record

VenueNature Communications · 2019
Typereview
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsSimon Fraser UniversityMemorial University of Newfoundland
FundersH2020 Marie Skłodowska-Curie ActionsUniversity of BristolNatural Environment Research CouncilEuropean CommissionSight Research UKLeverhulme Trust
KeywordsCarbon cycleBiogeochemical cycleGreenhouse gasEarth scienceWeatheringEnvironmental scienceCarbon fibersGlobal warmingCyclingIce sheetAtmosphere (unit)Carbon sequestrationAtmospheric sciencesNutrient cycleGreenhouse effectClimate changeCarbon dioxideEcologyOceanographyNutrientEnvironmental chemistryGeologyChemistryEcosystemMaterials scienceGeographyMeteorologyGeomorphologyBiology

Abstract

fetched live from OpenAlex

Abstract The cycling of carbon on Earth exerts a fundamental influence upon the greenhouse gas content of the atmosphere, and hence global climate over millennia. Until recently, ice sheets were viewed as inert components of this cycle and largely disregarded in global models. Research in the past decade has transformed this view, demonstrating the existence of uniquely adapted microbial communities, high rates of biogeochemical/physical weathering in ice sheets and storage and cycling of organic carbon (>104 Pg C) and nutrients. Here we assess the active role of ice sheets in the global carbon cycle and potential ramifications of enhanced melt and ice discharge in a warming 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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.049
GPT teacher head0.394
Teacher spread0.344 · 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
GenreReview

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

Citations225
Published2019
Admission routes1
Has abstractyes

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