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Record W4414987208 · doi:10.1029/2025gl119790

Microbial Controls on Dissolved Organic Nitrogen Cycling During Long‐Term Degradation Experiments

2025· article· en· W4414987208 on OpenAlexafffundabout
Richard A. LaBrie, Roxane Maranger, Luc Tremblay, Jennifer Cherrier, Jean‐Éric Tremblay, Nagissa Mahmoudi

Bibliographic record

VenueGeophysical Research Letters · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsUniversité LavalUniversité de MonctonMcGill UniversityBureau de Coopération Interuniversitaire
FundersFonds de recherche du Québec – Nature et technologiesMcGill Space InstituteNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsDissolved organic carbonDegradation (telecommunications)NitrogenCyclingMicrobial biodegradationCarbon fibersTotal organic carbon

Abstract

fetched live from OpenAlex

Abstract Dissolved organic nitrogen (DON) is critical for marine microbial growth by providing carbon and nitrogen. Although DON is rapidly cycled, some compounds within this pool can persist for long‐periods of time. To better understand how DON is cycled by marine microorganisms, we conducted 548‐day incubations using surface‐derived dissolved organic matter along with microbial communities from the surface, mesopelagic, and bathypelagic regions of the Labrador Sea. Across all depths, and even when corrected for particulate production, ∼2 μmol L −1 DON was produced and persisted for several months (i.e., semilabile DON), with ∼20% attributed to cell growth‐and‐death cycles and ∼80% to direct exudation by microbial communities. This newly synthesized DON was subsequently transformed by microbial communities, indicated by increased protein‐like fluorescence and decreased amino acids contribution to DON. These findings suggest that microbial communities can produce transiently persistent DON with potential implications for nitrogen storage and recycling in the ocean's interior.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.022
GPT teacher head0.299
Teacher spread0.277 · 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 designBench or experimental
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

Citations0
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueGeophysical Research Letters→Same topicWastewater Treatment and Nitrogen Removal→French-language works237,207→