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Record W4292448889 · doi:10.1101/2022.08.09.503387

Hydrogen and dark oxygen drive microbial productivity in diverse groundwater ecosystems

2022· preprint· en· W4292448889 on OpenAlexafffundabout
S. Emil Ruff, Pauline Humez, Isabella Hrabě de Angelis, Michael Nightingale, Muhe Diao, Sara Cho, Liam Connors, Olukayode Kuloyo, Alan Seltzer, Samuel Bowman, Scott D. Wankel, Cynthia McClain, Bernhard Mayer, Marc Strous

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsAlberta Environment and Protected AreasUniversity of Calgary
FundersAlberta InnovatesAlberta Innovates - Technology FuturesAlberta Parks
KeywordsGroundwaterAnoxic watersEcosystemEnvironmental chemistryEnvironmental scienceAquiferPopulationMethaneEcologyHydrology (agriculture)ChemistryGeologyBiology

Abstract

fetched live from OpenAlex

Groundwater ecosystems are globally wide-spread yet still poorly understood. We investigated the age, aqueous geochemistry, and microbiology of 138 groundwater samples from 87 monitoring wells (<250m depth) located in 14 aquifers in the Canadian Prairie. Geochemistry and microbial ecology were tightly linked revealing large-scale aerobic and anaerobic hydrogen, methane, nitrogen, and sulfur cycling carried out by diverse microbial communities. Older groundwaters contained on average more cells (up to 1.4×10 7 /mL) than younger ground-waters. Organic carbon-rich strata featured some of the highest abundances, challenging current estimates of global groundwater population sizes. Substantial concentrations of dissolved oxygen (n=57; 0.52±0.12 mg/L [mean±SE]; 0.39 mg/L [median]) in older groundwaters could support aerobic lifestyles in subsurface ecosystems at an unprecedented scale. Metagenomics, oxygen isotope analyses and mixing models indicated that microbial “dark oxygen” contributed to the dissolved oxygen pool in subsurface ecosystems commonly assumed to be anoxic.

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)0.000
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 score0.065
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.009
GPT teacher head0.191
Teacher spread0.182 · 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

Citations9
Published2022
Admission routes3
Has abstractyes

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