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Record W2320145109 · doi:10.1520/acem20140024

Development of Design Gyration Levels for Airfield Asphalt Pavement

2015· article· en· W2320145109 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

VenueAdvances in Civil Engineering Materials · 2015
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsGyrationAsphaltAsphalt pavementHammerGeotechnical engineeringCompactionMaterials scienceStructural engineeringEngineeringComposite materialMechanical engineering

Abstract

fetched live from OpenAlex

Abstract The objective of this paper is to provide guidance for adapting Superpave gyratory compactor (SGC) procedures to design airfield asphalt mixes (specifically to select the design asphalt content) with comparable properties to Item P-401 protocol. Three methods were used for selecting the SGC design compactive effort: (1) evaluate in-place density in the general manner used during development of the Marshall mix design airfield procedure; (2) compare specimen bulk specific gravities compacted with the Marshall hammer and SGC; and (3) test airfield mixes using confined repeated load permanent deformation testing to determine the binder content at which the mixtures become unstable. The result of this analysis was a gyration level related to tire pressure.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.703
Threshold uncertainty score0.756

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 communication0.0000.001
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 head0.059
GPT teacher head0.288
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