MétaCan
Menu
Back to cohort
Record W4256408943 · doi:10.5194/bgd-10-2245-2013

A new estimate of ocean oxygen utilization points to a reduced rate of respiration in the ocean interior

2013· preprint· en· W4256408943 on OpenAlexafffund
Olaf Duteil, Wolfgang Koeve, Andreas Oschlies, Daniele Bianchi, Iris Kriest, Eric D. Galbraith, Richard J. Matear

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicOcean Acidification Effects and Responses
Canadian institutionsMcGill University
FundersDeutsche ForschungsgemeinschaftBundesministerium für Bildung und ForschungCompute CanadaNatural Sciences and Engineering Research Council of CanadaCanadian Institute for Advanced Research
KeywordsOxygenBiogeochemical cycleRespirationApparent oxygen utilisationEnvironmental scienceAtmosphere (unit)Oxygen evolutionOceanographyAtmospheric sciencesChemistryEnvironmental chemistryGeologyBiologyMeteorologyBotanyGeography

Abstract

fetched live from OpenAlex

Abstract. The Apparent Oxygen Utilization (AOU) is a classical measure of the amount of oxygen respired by biological processes in the ocean interior. We show that the AOU systematically overestimates the True Oxygen Utilization (TOU) in 6 coupled circulation-biogeochemical ocean models, due to atmosphere–ocean oxygen disequilibrium in the subduction regions, consistent with prior work. We develop a new approach that we call Evaluated Oxygen Utilization (EOU), which approximates the TOU at least twice as well as AOU in all 6 models, despite large differences in the physical and biological components of the models. Applying the EOU approach to a global observational dataset leads to an estimated biological oxygen consumption rate that is by 25 percent lower than that derived from AOU-based estimates.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.737
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.045
GPT teacher head0.291
Teacher spread0.246 · 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 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

Citations1
Published2013
Admission routes2
Has abstractyes

Explore more

Same topicOcean Acidification Effects and ResponsesFrench-language works237,207