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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 (>10 4 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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.905
Threshold uncertainty score0.999

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 science0.0030.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.002

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 teacher head, not a consensus.

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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