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Record W2313071246 · doi:10.1061/40885(215)5

A Decade of Shotcrete Research at Laval University

2006· article· en· W2313071246 on OpenAlexaffabout
Marc Jolin, Benoı̂t Bissonnette

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsShotcreteDurabilityAir entrainmentEngineeringCivil engineeringConstruction engineeringGeotechnical engineeringComputer scienceDatabase

Abstract

fetched live from OpenAlex

This paper presents some of the most interesting outcomes of over a decade of shotcrete research at the Department of Civil Engineering, Laval University (Quebec City, Canada). While focusing mainly on dry-mix shotcrete, the paper also covers experimental work done on fresh and hardened properties of wet-mix shotcrete. Topics presented include rheological interpretation of the influence of fresh properties of shotcrete on placement and performance, effects of certain mixture design parameters (presence of accelerator, use of air-entraining admixture, etc.) on strength and durability, and effect of reinforcement encapsulation on performance. Key experimental observations, typical results, and recommendations are presented. Illustrations from actual field practices as well as ongoing research are provided.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.990
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.003
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0150.003

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 head0.028
GPT teacher head0.257
Teacher spread0.229 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2006
Admission routes2
Has abstractyes

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