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Numerical Model for Biological Oxidation and Migration of Methane in Soils

2001· article· en· W2034022534 on OpenAlex

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

VenuePractice Periodical of Hazardous Toxic and Radioactive Waste Management · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMethaneSoil waterAnaerobic oxidation of methaneEnvironmental scienceGreenhouse gasSoil scienceMoistureWater contentLimitingFlux (metallurgy)Environmental chemistryEnvironmental engineeringChemistryGeologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Concern over the potentially negative impacts of climate change has resulted in a search for techniques to reduce anthropogenic emissions of methane, a primary greenhouse gas. Microbial oxidation of methane in soils may serve as an inexpensive technique for reducing CH4 emissions from sources such as landfills and heavy oil wells. To gain a better quantitative understanding of the biological and physical processes limiting CH4 oxidation in soils and biofilters, a numerical reactive-transport model was developed. The model inputs include CH4 source strength, soil bulk density, moisture content, and biological kinetic parameters. The outputs consist of gas concentration profiles, CH4 oxidation rates, and surface flux rates. A series of soil column and batch incubation experiments were performed on a variety of soil types to calibrate and verify the model. The model was also verified by reproducing experimental results found in the literature.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score0.444

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 head0.021
GPT teacher head0.271
Teacher spread0.250 · 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