MétaCan
Menu
Back to cohort

Compression Behavior of Large-Sized Tire-Derived Aggregate for Embankment Application

2012· article· en· W2079658582 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Materials in Civil Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsCanadian Natural Resources
Fundersnot available
KeywordsCompression (physics)Aggregate (composite)CompressibilityMaterials scienceCompression testStructural engineeringComposite materialGeotechnical engineeringEngineering

Abstract

fetched live from OpenAlex

Tire-derived aggregate (TDA) has been successfully used for highway embankment applications in the past. Previous applications mainly used small and medium tire sizes as TDA sources. There are no published test results in the literature regarding the compression behavior of TDA made solely from off-the-road tires (OTR). In this study, large-scale, one-dimensional compression tests are carried out to study the compression behavior of TDA from OTR as well as from passenger and light-truck tires (PLTT). Samples for the tests are prepared by varying the initial unit weights. The results show that there is a general trend of decreasing compressibility with increasing initial unit weight for both TDA sources. The compression test results are also used to compare compression behavior between the two TDA sources. It is found that the compression behavior of TDA from OTR and PLTT is more or less similar. Moreover, one-dimensional stress-strain regression equations were developed for TDA from OTR.

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.

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)0.001
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 score0.196
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.010
GPT teacher head0.239
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