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Record W4230070489 · doi:10.32920/ryerson.14645955

Studies on the fresh properties an durability of unshrinkable fill containing recycled concrete aggregate or natural aggregates of marginal quality

2021· preprint· en· W4230070489 on OpenAlexaff
Maryam Kolahdoozan

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicRecycled Aggregate Concrete Performance
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsEttringiteGypsumAggregate (composite)DurabilityMaterials scienceCarbonationAbrasion (mechanical)Slag (welding)Hardening (computing)Composite materialMetallurgyCementPortland cement

Abstract

fetched live from OpenAlex

The intention of this research is to explore the feasibility of incorporating aggregates of low or marginal quality, such as Recycled Concrete Aggregate (RCA) and aggregate with high sulphate content, in U-fill mixtures. It has been determined that where RCA is used, water dissipation may be hindered due to the increase in fines caused by abrasion, hence causing an increase in hardening time. To reduce this effect, addition of natural aggregates may be necessary. Moreover, through a series of investigation it has been found that high percentages of sulphate may cause severe damage due to Ettringite and Thaumasite formation; however by incorporation of supplementary materials such as slag the deleterious effects of internal sulphate attack can be reduced. The effects of using Na2SO4 and gypsum in the presence of slag have also been investigated. Results indicated that due to the lower available calcium content within bars containing Na2SO4 expansion rate is low.

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)0.000
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.092
GPT teacher head0.306
Teacher spread0.214 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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