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Record W2906917992 · doi:10.1111/gbi.12325

Rates and pathways of CH<sub>4</sub> oxidation in ferruginous Lake Matano, Indonesia

2018· article· en· W2906917992 on OpenAlex
Arne Sturm, David A. Fowle, CarriAyne Jones, Karla Leslie, Sulung Nomosatryo, Cynthia Henny, Donald E. Canfield, Sean A. Crowe

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGeobiology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsUniversity of British Columbia
FundersNational Research FoundationDanmarks GrundforskningsfondVillum FondenNational Science Foundation
KeywordsGeochemistryGeologyEnvironmental scienceEarth science

Abstract

fetched live from OpenAlex

Abstract This study evaluates rates and pathways of methane (CH 4 ) oxidation and uptake using 14 C‐based tracer experiments throughout the oxic and anoxic waters of ferruginous Lake Matano. Methane oxidation rates in Lake Matano are moderate (0.36 nmol L −1 day −1 to 117 μmol L −1 day −1 ) compared to other lakes, but are sufficiently high to preclude strong CH 4 fluxes to the atmosphere. In addition to aerobic CH 4 oxidation, which takes place in Lake Matano's oxic mixolimnion, we also detected CH 4 oxidation in Lake Matano's anoxic ferruginous waters. Here, CH 4 oxidation proceeds in the apparent absence of oxygen (O 2 ) and instead appears to be coupled to some as yet uncertain combination of nitrate ( ), nitrite ( ), iron (Fe) or manganese (Mn), or sulfate ( ) reduction. Throughout the lake, the fraction of CH 4 carbon that is assimilated vs. oxidized to carbon dioxide (CO 2 ) is high (up to 93%), indicating extensive CH 4 conversion to biomass and underscoring the importance of CH 4 as a carbon and energy source in Lake Matano and potentially other ferruginous or low productivity environments.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score0.449

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 science0.0000.000
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 head0.010
GPT teacher head0.209
Teacher spread0.199 · 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