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2025· peer-review· W4415300241 on OpenAlexaboutno aff
Lennart Gerke

Bibliographic record

Venuenot available
Typepeer-review
Language
FieldBiochemistry, Genetics and Molecular Biology
TopicSignaling Pathways in Disease
Canadian institutionsnot available
Fundersnot available
KeywordsDeep waterNorth Atlantic Deep WaterBiogeochemical cycleWater massCurrent (fluid)EstuaryDeep sea

Abstract

fetched live from OpenAlex

<strong class="journal-contentHeaderColor">Abstract.</strong> The deep waters of the Gulf of St. Lawrence (GSL) have experienced a significant reduction in dissolved oxygen content during the past decades. One widely documented driver of this deoxygenation is a change in the composition of the deep inflowing water that ventilates the Gulf. This deep water is known to consist of a mix of warmer, less-oxygenated North Atlantic Central Waters (NACW) and cooler, more-oxygenated Labrador Current Waters (LCW), with prior studies inferring a shift towards increased NACW contribution. However, this compositional change has only ever been inferred indirectly from physical and biogeochemical measurements via the use of inverse methods such as water mass analysis. In this study, we present results from the first spatially-comprehensive deep water transient tracer surveys in the GSL, allowing us to directly map mean age estimates and use these to infer recent changes in the composition of regional deep waters. The results reveal an unexpected age distribution, with 'older' deep waters present near the Gulf's entrance, whereas 'younger' water is found further inshore, contrary to the expected estuarine circulation pattern, which transports deep water inland (increasing age along the flow path). This implies a gradual increase in the proportion of NACW from inshore areas towards the Gulf's entrance and provides direct evidence that the shift towards NACW dominated deep waters is ongoing as of 2022, contrary to earlier predictions of the complete disappearance of the younger, well-oxygenated LCW.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.297
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.021
GPT teacher head0.315
Teacher spread0.294 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

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