MétaCan
Menu
Back to cohort
Record W2476855388 · doi:10.1680/jcoma.15.00020

Influence of cement alkalis on mortar expansion of ASTM C 1260

2016· article· en· W2476855388 on OpenAlexaff
Mohammad S. Islam, Nader Ghafoori

Bibliographic record

VenueProceedings of the Institution of Civil Engineers - Construction Materials · 2016
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsHamilton Regional Laboratory Medicine Program
FundersNevada Department of Transportation
KeywordsMortarAlkali–aggregate reactionSodium hydroxideAlkali metalCementAggregate (composite)Alkali–silica reactionMaterials scienceCalcium hydroxideHydroxideMineralogyChemistryComposite materialInorganic chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The main objective of this study was to evaluate the influence of three dosages of cement alkalis, such as 0·42, 0·84 and 1·26% Na 2 O eq , on the alkali–silica reactivity-induced expansion of mortar bars prepared with 14 aggregate groups for 1·0, 0·5 and 0·25 N sodium hydroxide solutions at test durations of 14, 28, 56 and 98 d. For each alkali solution, the percentage contribution of cement alkali, test duration and their interaction to mortar expansion was also evaluated. The study revealed that, regardless of aggregate mineralogy, the influence of cement alkalis on mortar expansion depended mainly on the alkali solution concentration and test duration. The effect was more severe for the reduced concentration of alkali solution and early test duration, whereas the influence was minor for higher concentrations of alkali solution and extended test durations. Elevating cement alkalis resulted in a greater increase in the expansion of reactive aggregates for 0·25 N sodium hydroxide as compared to that of innocuous aggregates.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.444

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 communication0.0000.000
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 head0.211
Teacher spread0.202 · 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 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

Citations4
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Institution of Civil Engineers - Construction MaterialsSame topicConcrete and Cement Materials ResearchFrench-language works237,207