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Record W4229364026 · doi:10.3989/mc.2022.16221

Alkali-silica reaction in volcanic rocks: a worldwide comparative approach

2022· article· en· W4229364026 on OpenAlexafffundabout
Sara Medeiros, Isabel Fernandes, Benoît Fournier, João Carlos Nunes, António Santos Silva, Violeta Ramos, D. Soares

Bibliographic record

VenueMateriales de Construcción · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversité Laval
FundersUniversité LavalEuropean Regional Development FundEuropean Social FundFundação para a Ciência e a TecnologiaInterregNatural Sciences and Engineering Research Council of CanadaFundo Regional para a Ciência e Tecnologia
KeywordsVolcanoAggregate (composite)PetrographyMortarAlkali–aggregate reactionAlkali–silica reactionVolcanic rockGeologyReactivity (psychology)BasaltGeochemistryEarth scienceMineralogyEnvironmental scienceMaterials scienceOceanographyComposite material

Abstract

fetched live from OpenAlex

The potential alkali-silica reactivity (ASR) of volcanic aggregates, especially basalts, remains a source of debate in the scientific community. When evaluating the potentially deleterious character of this type of aggregate, different laboratory testing methods may produce contradictory data; this is particularly evident when using the accelerated mortar bar test (AMBT). In order to better understand such discrepancies, this study applied several methods of characterizing potential aggregate alkali reactivity, including the accelerated mortar bar test (AMBT), petrographic characterization, and the concrete prism test (CPT). Moreover, this study assessed volcanic aggregate samples from sites around the world, including the Azores, Brazil, Canada, the Canary and Hawaiian Islands, Iceland, Japan, Mozambique, New Zealand, Norway, and Turkey. The results obtained contribute to accurately assessing the potential alkali reactivity of volcanic aggregates and enhance the understanding of their different behaviours.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0140.008
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.019
GPT teacher head0.211
Teacher spread0.192 · 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 designObservational
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

Citations8
Published2022
Admission routes3
Has abstractyes

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