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Record W4409255211 · doi:10.1021/acsestair.4c00302

Selective Ocean–Atmosphere Bacterial Flux Through the Pacific Sea Surface Microlayer

2025· article· en· W4409255211 on OpenAlexaff
Ariel C. Tastassa, Yael Dubowski, Or Argaman Meirovich, Irina Kuzmenkov, Naama Lang‐Yona

Bibliographic record

VenueACS ES&T Air · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAtmosphere (unit)Flux (metallurgy)OceanographyEnvironmental scienceCarbon fluxPacific oceanClimatologyAtmospheric sciencesGeologyGeographyMeteorologyChemistryBiologyEcosystem

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide Marine–atmosphere microbial exchange is essential for nutrient cycling and ecosystem dynamics, though mechanisms are poorly understood. The role of the sea surface microlayer (SML) in mediating these exchanges was investigated. Samples were collected across a latitude gradient in the Pacific Ocean, and 16S rRNA gene and transcript sequences from surface seawater (SW), SML, and atmospheric samples were analyzed. The genomic signature varied diurnally and spatially, with the SW community being the most consistent and the air community the most variable. The SML displayed genomic characteristics intermediate between SW and air. The 16S rRNA transcript signature, a proxy for active microbial communities, showed tight clustering in the air and SML, suggesting selective control compared to SW. The transcriptional community composition in the air clustered between the SML and SW, pointing to viable non-SML-mediated exchange. Furthermore, taxa from air- and marine-associated communities showed a gradient of presence through all three environments, suggesting an exchange of key species through the SML. Additionally, certain volatile organic compounds in the atmosphere demonstrated a noteworthy relationship with specific bacterial taxa in the SML. This study improves our understanding of the role of the SML in ocean–atmosphere exchanges of marine bacteria and highlights how microbial communities travel and best utilize their environment.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.007
GPT teacher head0.223
Teacher spread0.216 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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