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Record W4287838603 · doi:10.32920/20365674.v1

A Proposed Laboratory Method to Evaluate the Durability of Concrete Pavement Joints Against Freezing in the Presence of Deicer Salts

2022· preprint· en· W4287838603 on OpenAlexafffund
Ramy Elbakari, Medhat Shehata

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsToronto Metropolitan University
FundersMinistère des Transports
KeywordsDurabilitySlabJoint (building)Flexural strengthWettingMaterials scienceComposite materialReinforced concreteSalt (chemistry)Geotechnical engineeringEnvironmental scienceStructural engineeringChemistryGeologyEngineering

Abstract

fetched live from OpenAlex

<p> Deicer salts were found to cause deterioration to the concrete pavement, particularly at joints. This paper introduces a laboratory procedure that engineers and scientists can use to evaluate the durability of joints. Concrete samples were tested under different salt concentrations and exposure conditions, including freeze-thaw cycles, wet-dry cycles, and a combination thereof. The test sample comprises a square slab measuring 200x200x120 mm and a joint running in the middle at 40 mm depth. The results showed that the test method needs to include two salts with two exposure conditions for accelerated damage. The first exposure uses NaCl at 10% concentration with 50 cycles of freeze/thaw-wet/dry alternating every five consecutive cycles. The second exposure uses CaCl2 at 15% concentration with 50 cycles of wetting and drying at 5°C and 35 °C, respectively. Damage is assessed using two approaches: 1) strength loss under flexural loading and 2) visual damage </p>

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)0.008
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 score0.300
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
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 science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.296
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

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
Published2022
Admission routes2
Has abstractyes

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