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Record W2715989322

Characterization of Indian and Canadian Fly Ash for Use in Concrete

2017· dissertation· en· W2715989322 on OpenAlexaboutno aff
Yasar Abualrous

Bibliographic record

VenueTSpace (University of Toronto) · 2017
Typedissertation
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsnot available
FundersMinistry of EnvironmentMinistry of Environment and Forests
KeywordsFly ashCharacterization (materials science)Environmental scienceWaste managementEngineeringMaterials scienceNanotechnology
DOInot available

Abstract

fetched live from OpenAlex

The chemical, physical, and morphological properties of fly ash samples from nine Indian and Canadian coal-fired stations were characterized in this research work. The effect of particle size distribution, not adequately addressed in the standards and the literature, on water requirement and pozzolanic activity of the various fly ash samples was examined. The particle size distributions for the nine Indian and Canadian sources were measured using Laser Diffraction Analyzer (LDA). Each LDA measurement was verified by a corresponding scanning electron micrograph. Particle size analysis appears critical to determining the suitability of the practices presently in use for collection and processing fly ash. The effects of fly ash variability on concrete properties were determined within three series of experiments. The findings of this study have potential to form the basis for drafting recommendations to modify existing prescribed limits in the standard specifications for fly ash for use in cement and concrete.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.400
Threshold uncertainty score0.805

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.237
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueTSpace (University of Toronto)→Same topicConcrete and Cement Materials Research→French-language works237,207→