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Record W2030098211 · doi:10.1520/gtj11121j

Oxygen Diffusion Coefficient of Soils at High Degrees of Saturation

2000· article· en· W2030098211 on OpenAlexaff
Mengxing Lin, EK Yanful

Bibliographic record

VenueGeotechnical Testing Journal · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicMine drainage and remediation techniques
Canadian institutionsWestern University
Fundersnot available
KeywordsSaturation (graph theory)Soil waterSoil scienceDiffusionHumidityOxygenEffective diffusion coefficientDegree of saturationEnvironmental scienceChemistryMaterials scienceMineralogyThermodynamicsMathematics

Abstract

fetched live from OpenAlex

Abstract The oxygen diffusion coefficient is an essential parameter for design of soil covers over mine waste. This study presents a method for measuring the oxygen diffusion coefficient of soils at high degrees of saturation. The method eliminates measurement errors caused by soil microbial activity, high humidity, and stagnant air in laboratory diffusion cells. Results show that microbial activity is an important factor that causes errors in O2 measurements. Sterilization of soil, utilization of a silica gel-membrane system with oxygen sensors, and minimal stirring in the cell headspace greatly reduce the variability in O2 diffusion coefficient measurements. The variations in estimated O2 diffusion coefficients for the same soil at the same degree of saturation were ±31% about the mean for clayey soil samples and ±10% about the mean for silty soil samples.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.449
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0030.000

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 head0.015
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 teacher head, not a consensus.

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

Citations11
Published2000
Admission routes1
Has abstractyes

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