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Record W6996840137

THERMAL PROPERTIES AND SOIL-WATER CHARACTERISTIC CURVES OF COAL FLY ASH AND MINE TAILINGS MIXTURES

2011· article· en· W6996840137 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2011
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsTailingsFly ashCoalCoal miningThermalThermal power station
DOInot available

Abstract

fetched live from OpenAlex

The results of a pilot test carried out near a tailings disposal pond at the Musselwhite Mine, Northern Ontario, Canada are analyzed in this thesis to study the application of coal fly ash in mine tailings under the natural setting. A set of water content and temperature data is collected from four tanks at the test site filled with mine tailings\n(Tank A), coal fly ash and mine tailings in a stratified approach (Tank B), and coal fly ash and mine tailings mixtures in mass ratios of 10:90 (Tank C) and 15:85 (Tank D), respectively. These data are analyzed in this thesis. Furthermore, the thermal properties of mine tailings and mixtures of coal fly ash and mine tailings are measured by a thermal properties analyzer, and their soil-water characteristic curves are developed by the filter paper method in the lab. The results from the lab tests are correlated to the field\nobservation to enhance the understanding of field application of coal fly ash in the management of reactive mine tailings.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.900

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 communication0.0000.001
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 head0.078
GPT teacher head0.225
Teacher spread0.147 · 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.

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
Published2011
Admission routes1
Has abstractyes

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