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Record W2091939918 · doi:10.1029/1999pa000422

Glacial‐interglacial variability in denitrification in the World's Oceans: Causes and consequences

2000· article· en· W2091939918 on OpenAlexaff
Raja S Ganeshram, Thomas F. Pedersen, Stephen E. Calvert, Gavin W. McNeill, Michel Fontugne

Bibliographic record

VenuePaleoceanography · 2000
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of British Columbia
FundersNational Science Foundation
KeywordsGlacial periodInterglacialDenitrificationOceanographyGeologyWater columnUpwellingOxygen minimum zoneDeep seaNitrogenPaleontologyChemistry

Abstract

fetched live from OpenAlex

The late Quaternary history of water‐column denitrifcation of the eastern Pacific margins and the Arabian Sea is reconstructed using sedimentary δ 15 N measurements. The δ 15 N values in six piston cores raised from these regions show remarkably similar cyclic variations, being heavy (9–10.5‰) during the interglacials and 2–3‰ lighter during the glacials. This implies that denitrification in these regions decreased substantially during the glacial periods. The glacial decline in denitrification is attributed to reduced upwelling and flux of organic material through the oxygen minimum zone. Since water‐column denitrification in these areas accounts for about half of the fixed‐nitrogen loss in the modern ocean, the inferred decrease in denitrification should have increased the oceanic nitrate inventory during glacial periods. Because nitrate is a limiting nutrient, oceanic productivity and attendant changes in CO 2 may therefore have been modulated on glacial‐interglacial timescales by variations in the oceanic NO 3 content.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.016
GPT teacher head0.251
Teacher spread0.235 · 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

Citations292
Published2000
Admission routes1
Has abstractyes

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