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Record W4381930739 · doi:10.1038/s43247-023-00891-6

Thermochemical oxidation of methane by manganese oxides in hydrothermal sediments

2023· article· en· W4381930739 on OpenAlexaff
Qin Huang, Shao‐Yong Jiang, Dao-Hui Pi, Kurt O. Konhauser, Xingping Wen, Liuyi Lu

Bibliographic record

VenueCommunications Earth & Environment · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsUniversity of Alberta
FundersNational Natural Science Foundation of China
KeywordsRhodochrositeAnaerobic oxidation of methaneMethaneHydrothermal circulationGeochemistryGeologyDiagenesisEnvironmental chemistryChemistryCalcite

Abstract

fetched live from OpenAlex

Abstract Microbial anaerobic oxidation of methane coupled to the reduction of Mn(IV)-oxides, typically MnO 2 , derived from continental weathering and riverine transport has been proposed as a globally important sink of methane. However, the potential role of hydrothermal Mn(IV) oxide-rich sediments as a methane sink, and the mechanisms of underpinning methane oxidation at high-temperature hydrothermal fields remain poorly understood. Here, we report the occurrence of almost pure rhodochrosite with extremely negative δ 13 C PDB values (as low as –76.4‰) in direct association with hausmannite formed through hydrothermal activity in the Late Triassic Heqing Mn deposit in Southern China. Based on detailed petrography and geochemistry, this rhodochrosite is interpreted as the result of the thermochemical oxidation of methane by hausmannite during early diagenesis. Given high hydrothermal Mn 2+ and CH 4 release coupled to low sulfate concentration observed in the Archean oceans, we propose that hydrothermal Mn(IV) oxides may have been effective methane sinks in Earth’s ancient oceans.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.017
GPT teacher head0.242
Teacher spread0.225 · 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 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

Citations13
Published2023
Admission routes1
Has abstractyes

Explore more

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