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Record W4400921783 · doi:10.1038/s43247-024-01561-x

Distinct sources of uncertainty in simulations of the ocean biological carbon pump at different depths

2024· article· en· W4400921783 on OpenAlexafffund
Bin Wang, Katja Fennel

Bibliographic record

VenueCommunications Earth & Environment · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaOcean Frontier Institute
KeywordsBiological pumpCarbon fibersEnvironmental scienceOceanographyCarbon cycleGeologyEcologyComputer scienceBiologyEcosystem

Abstract

fetched live from OpenAlex

Abstract Model uncertainty in simulating the biological carbon pump was quantified and partitioned using 14 models from the Coupled Model Intercomparison Project Phase 6. Uncertainty increases with depth. On the global scale, uncertainty in carbon export dominates above 900 m and uncertainty in transfer efficiency below. Reducing model uncertainty in carbon export and transfer efficiency offers similar benefits for understanding century-scale carbon sequestration and climate. These models produce three different qualitative patterns in transfer efficiency: one where it is globally homogenous and two opposite latitudinal patterns due to different model structures and parameters. The exponent b of the Martin curve, which has long been used to compare different representations of transfer efficiency, is shown here to underestimate uncertainty in transfer efficiency. This highlights the importance of using vertical profiles of carbon flux rather than the single exponent b in model validation and intercomparison exercises.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.690

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 head0.025
GPT teacher head0.213
Teacher spread0.188 · 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

Citations7
Published2024
Admission routes2
Has abstractyes

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