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Record W2766099597 · doi:10.1002/2017gl075157

Oxygen Minimum Zone Contrasts Between the Arabian Sea and the Bay of Bengal Implied by Differences in Remineralization Depth

2017· article· en· W2766099597 on OpenAlexfundno aff
Muchamad Al Azhar, Zouhair Lachkar, Marina Lévy, K. Shafer Smith

Bibliographic record

VenueGeophysical Research Letters · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsnot available
FundersYork UniversityNew York University Abu Dhabi
KeywordsOxygen minimum zoneBayDenitrificationOceanographyOxygenEnvironmental scienceWater columnBENGALGeologyAtmospheric sciencesNitrogenChemistry

Abstract

fetched live from OpenAlex

Abstract The combination of high primary productivity and weak ventilation in the Arabian Sea (AS) and Bay of Bengal (BoB) generates vast areas of depleted oxygen, known as oxygen minimum zones (OMZs). The AS OMZ is the world's thickest and hosts up to 40% of global denitrification. In contrast, the OMZ in the BoB is weaker and denitrification free. Using a series of model simulations, we show that the deeper remineralization depth (RD) in the BoB, potentially associated with organic matter aggregation with riverine mineral particles, contributes to weaken its OMZ. When the RD is set uniformly across both seas, the model fails to reproduce the observed contrast between the two OMZs, irrespective of the chosen RD. In contrast, when the RD is allowed to vary spatially, the contrasting distributions of oxygen and nitrate are correctly reproduced, and water column denitrification is simulated exclusively in the AS, in agreement with observations.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.194

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.032
GPT teacher head0.269
Teacher spread0.237 · 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 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

Citations63
Published2017
Admission routes1
Has abstractyes

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