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Record W1629767359 · doi:10.1029/2005gb002489

A factorial analysis of the marine carbon cycle and ocean circulation controls on atmospheric CO<sub>2</sub>

2005· article· en· W1629767359 on OpenAlexaff
David Cameron, Timothy M. Lenton, Andy Ridgwell, J. G. Shepherd, Robert Marsh, Andrew Yool

Bibliographic record

VenueGlobal Biogeochemical Cycles · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of British Columbia
FundersNatural Environment Research Council
KeywordsCarbonateCarbon cycleEnvironmental scienceSolubilityAtmospheric circulationOcean currentCirculation (fluid dynamics)Factorial experimentTotal organic carbonOceanographyCarbon dioxideAtmospheric sciencesClimatologyChemistryEnvironmental chemistryGeologyThermodynamicsEcology

Abstract

fetched live from OpenAlex

A factorial experiment with a new Earth system model of intermediate complexity is used to assess the sensitivity of atmospheric CO2 to organic, carbonate and solubility pumps, ocean circulation state, and climate feedback. An analysis of variance of the results reveals that the organic, carbonate, and solubility pumps act multiplicatively and account for 94% of the variance of atmospheric CO2. The organic pump explains 63% (89 ppm), the solubility pump 24% (55 ppm), the carbonate pump 6% (28 ppm), and ocean circulation 0.3% (12 ppm) of the variance. Removing all pumps increases atmospheric CO2 from 278 to 525 ppm. Including interactions with all the pumps increases the effects of ocean circulation from 12 to 56 ppm. However, the ocean circulation states used are unlikely to span the full range of possible states. Changes in Pacific circulation have more effect on atmospheric CO2 than Atlantic circulation.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.004
GPT teacher head0.196
Teacher spread0.192 · 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

Citations52
Published2005
Admission routes1
Has abstractyes

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