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Record W4412617455 · doi:10.1016/j.cement.2025.100154

Condition assessment of pre-tensioning prestressed concrete sleepers distressed by internal swelling reactions (ISR)

2025· article· en· W4412617455 on OpenAlexafffund
R. Medeiros, Diego Jesus De Souza, Leandro Sanchez, Antônio Carlos Santos

Bibliographic record

VenueCement · 2025
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsUniversity of Ottawa
FundersUniversidade Federal de UberlândiaVale Canada Limited
KeywordsSwellingPrestressed concreteStructural engineeringMaterials scienceForensic engineeringEngineeringComposite material

Abstract

fetched live from OpenAlex

Concrete sleepers worldwide have been affected by internal swelling reactions (ISR), primarily alkali-silica reaction (ASR) and internal sulfate attack (ISA). While numerous studies have focused on diagnosing ISR-affected sleepers, most emphasize identifying the cause rather than estimating the extent of deterioration, which is critical for informed decision-making. This study presents a comprehensive condition assessment of concrete sleepers displaying numerous ages and environmental exposure conditions through visual inspection (i.e., crack measurements) followed by the implementation of the multi-level assessment protocol, composed of microscopic (i.e., damage rating index-DRI) and mechanical (i.e., stiffness damage test-SDT) testing procedures. Results evidenced the multi-level protocol efficiency in estimating the cause(s) (i.e., ASR+ISA), further confirmed through SEM-EDS analysis, and quantifying the deterioration extent. These findings reveal gaps in current specification to prevent ISR damage in new sleepers and the importance of considering environmental conditions in condition assessment of existing sleepers, demonstrating an urgent need to review specifications/protocols.

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 score0.441
Threshold uncertainty score0.568

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 head0.007
GPT teacher head0.266
Teacher spread0.260 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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