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Record W2010168368 · doi:10.1061/41095(365)79

Particle Size Analysis of Shale-Rich Mined Clay from Appalachian Ohio

2010· article· en· W2010168368 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

VenueGeoFlorida 2010 · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsGolder Associates (Canada)
Fundersnot available
KeywordsOil shaleSampling (signal processing)GeologyDrillingParticle-size distributionMining engineeringClay soilSoil testGrain sizeClay mineralsGeotechnical engineeringSoil waterSoil scienceParticle sizeMineralogyEngineeringGeomorphology

Abstract

fetched live from OpenAlex

Clayey soil found in coal mines in Appalachian Ohio is typically used for constructing Recompacted Soil Liners (RSL) in landfills. The suitability of mined clay for RSL in Ohio is first decided by its clay content. Even though the standard sampling and processing techniques should not produce different grain-size distributions, mined clay from Appalachian Ohio is an exception. This discrepancy poses a challenge to the geotechnical engineers who work on prequalification process of RSL material. This paper describes a laboratory investigation conducted on mined clay from Appalachian Ohio to determine how and why the standard sampling and/or processing methods affect the grain-size distributions. About a 10 percent decrease in the clay content was consistently observed in the samples obtained from clayey soil stockpiles, compared to those collected during reverse circulation drilling. It was discovered that the fragments of shale in underclay was responsible for the discrepancy.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0190.001

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 head0.007
GPT teacher head0.213
Teacher spread0.206 · 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