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Record W4417115215 · doi:10.5194/essd-17-6889-2025

Global inventory of doubly substituted isotopologues of methane (Δ <sup>13</sup> CH <sub>3</sub> D and Δ <sup>12</sup> CH <sub>2</sub> D <sub>2</sub> )

2025· article· en· W4417115215 on OpenAlexaff
Sara Defratyka, Julianne M. Fernandez, Getachew Agmuas Adnew, Guannan Dong, Peter Douglas, Daniel L. Eldridge, Giuseppe Etiope, Thomas Giunta, Mojhgan Haghnegahdar, A.N. Hristov, Nicole Hultquist, Iñaki Vadillo, Josué J. Jautzy, Ji‐Hyun Kim, Jabrane Labidi, Ellen Lalk, William D. Leavitt, Jiawen Li, Li‐Hung Lin, Jiarui Liu, Lucía Ojeda, Shuhei Ono, Jeemin H. Rhim, Thomas Röckmann, Barbara Sherwood Lollar, Malavika Sivan, Jiayang Sun, G. Todd Ventura, David T. Wang, Edward Young, Naizhong Zhang, Tim Arnold

Bibliographic record

VenueEarth system science data · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsSaint Mary's UniversityUniversity of TorontoGeological Survey of Canada
FundersNatural Environment Research CouncilEuropean Association of National Metrology Institutes
KeywordsIsotopologueMethanogenesisMethaneAtmospheric methaneIsotopeAnaerobic oxidation of methaneAtmospheric chemistryStable isotope ratio

Abstract

fetched live from OpenAlex

Abstract. Measurements of methane (CH4) molecules containing two rare isotopes (13CH3D and 12CH2D2), also termed doubly substituted or “clumped” isotopologues, have the potential to provide two additional isotopic dimensions to help investigate the mechanisms underlying global atmospheric trends in CH4. In this work, we summarise the current state of research on doubly substituted CH4 isotopologues, with an emphasis on compiling results of all relevant work. The database comprises 1475 records compiled from the literature published until April 2025 (https://doi.org/10.5285/51ae627da5fb41b8a767ee6c653f83e6, Defratyka et al., 2025). For field samples, 40 % of records were sourced from natural gas reservoirs, while microbial terrestrial (e.g., agriculture, lake, wetland) samples account only for 12.5 %. Lakes samples contribute 75 % to collected microbial terrestrial samples. There is limited or no representation of samples coming from significant microbial CH4 sources to the atmosphere, like wetlands, agricultural practices and landfills. To date, laboratory experiments were mostly focused on microbial (28 % of samples from laboratory experiments) and pyrogenic (15 %) methanogenesis or anaerobic (16 %), and aerobic (8 %) CH4 oxidation, with only single study of photochemical oxidation via OH and Cl, which constitutes 5 % of the laboratory experiments entries. The distinct ranges of Δ13CH3D and Δ12CH2D2 values measured in these studies suggests their potential to improve our understanding of atmospheric CH4. This work provides an overview of the major gaps in measurements and identifies where further studies should be focussed to enable the highest impact on understanding global CH4.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.010
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.001
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 head0.014
GPT teacher head0.232
Teacher spread0.217 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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