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Record W2160188316 · doi:10.1680/macr.2000.52.5.353

Controlling the quality of fresh concrete—a new approach

2000· article· en· W2160188316 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMagazine of Concrete Research · 2000
Typearticle
Languageen
FieldEngineering
TopicInnovations in Concrete and Construction Materials
Canadian institutionsNational Research Council CanadaCarleton UniversityMcMaster University
FundersNational Research Council Canada
KeywordsSlumpRheologyConcrete slump testGeotechnical engineeringShear rateViscosityConsistency (knowledge bases)Yield (engineering)Apparent viscosityMaterials scienceMeasure (data warehouse)Composite materialMathematicsGeologyComputer scienceCompressive strength

Abstract

fetched live from OpenAlex

Traditionally, the slump test has been used to measure concrete consistency. However, many researchers contend that the slump alone is not a sufficient measure of consistency and that other quantifiable rheological properties such as shear yield stress and plastic viscosity are more representative and should be considered. A SLump Rate Machine (SLRM) was adapted and calibrated, to consistently measure the plastic properties for a number of concrete mixes, namely slump rate and slump flow. Furthermore, a theoretical model was developed to correlate the slump flow and slump rate with the shear yield stress and plastic viscosity of fresh concrete, respectively. Employing the SLRM and the theoretical model has resulted in an efficient new approach to adequately predict the rheological behaviour of fresh concrete as well as to provide reasonably accurate values for shear yield stress and plastic viscosity.

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)0.003
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.079
GPT teacher head0.350
Teacher spread0.272 · 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