MétaCan
Menu
Back to cohort
Record W2038007663 · doi:10.1520/jai100432

Effect of Aggregate Particle Size on Determining Alkali-Silica Reactivity by Accelerated Tests

2006· article· en· W2038007663 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

VenueJournal of ASTM International · 2006
Typearticle
Languageen
FieldMaterials Science
TopicGraphite, nuclear technology, radiation studies
Canadian institutionsInstitute for Biological SciencesNatural Resources Canada
Fundersnot available
KeywordsAggregate (composite)Materials scienceAlkali–silica reactionParticle sizeReactivity (psychology)Particle (ecology)Alkali metalComposite materialChemical engineeringChemistryGeologyOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Abstract For assessing the rock applicability of accelerated tests for alkali-aggregate reactivity and the effect of aggregate particle size on determining alkali reactivity of concrete aggregates in accelerated tests, experimental studies on microstructure and expansion behaviors of Potsdam sandstone and a Norwegian quartzite were conducted in Concrete Prism Test and in various accelerated tests, i.e., Accelerated Mortar Bar Test, Chinese Autoclave Method, and Chinese Accelerated Mortar Bar Test. Results indicate that, in comparison with Concrete Prism Test results, the alkali expansivity of both rocks are generally underestimated in these accelerated tests. It is mainly attributed to the use of a large proportion of very fine aggregate particles in which the original microtexture characteristic of rocks was lost during sample preparation. The effects of microtexture and the particle size of aggregate on reasonable prediction of alkali expansivity of aggregates in concrete by accelerated tests were discussed.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.069
Threshold uncertainty score0.399

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.009
GPT teacher head0.281
Teacher spread0.271 · 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