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Evaluation Method of Segregation of Road Concrete

2012· article· en· W2079946921 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

VenueApplied Mechanics and Materials · 2012
Typearticle
Languageen
FieldEngineering
TopicCivil and Geotechnical Engineering Research
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsAggregate (composite)Degree (music)Section (typography)Structural engineeringCharacter (mathematics)Distribution (mathematics)Computer scienceGeotechnical engineeringMaterials scienceEngineeringMathematicsGeometryMathematical analysisComposite materialAcousticsPhysics

Abstract

fetched live from OpenAlex

To deal with the problem there was no strict evaluation method and standard, an experiment was designed to evaluate the segregation degree of road concrete. Furthermore, the status and index of segregation was determined too. The testing analyzed the distribute character of coarse aggregate in road concrete. Based on the method of digital image processing and the assumption that particles in fresh concrete conform to uniform distribution, a model that size of coarse aggregate against vertical section (the direction against vertical section of specimen) in concrete conforms to continuous distribution was established. Segregation degree—a parameter to characterize the degree of segregation of particles in concrete was proposed. Meanwhile,a reference standard to evaluation segregation degree was given.

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)0.002
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: none
Teacher disagreement score0.552
Threshold uncertainty score0.235

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.020
GPT teacher head0.275
Teacher spread0.256 · 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