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Record W572330766

SMA IN THE USA II : THE PREMIER FORUM FOR THE PREMIER HMA

2002· article· fr· W572330766 on OpenAlexaboutno aff
M B Cervarich

Bibliographic record

VenueHMAT: Hot Mix Asphalt Technology · 2002
Typearticle
Languagefr
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsSMA*AsphaltEngineeringPortland cementCivil engineeringForensic engineeringHistoryArchaeologyCementComputer science
DOInot available

Abstract

fetched live from OpenAlex

Stone Matrix Asphalt (SMA) was the subject of a recent workshop in Frederick, Maryland which featured researchers, consultants, suppliers, and contractors from thirty five states and eleven foreign countries. An historical overview of SMA from Europe, the U.S., and Canada opened the workshops. SMA puts asphalt in a competitive position with Portland cement concrete on high-type pavements that require high-performing surfacing. SMA is hard to work with and produce in the proper mix, but when done right it performs outstandingly. The article also looks at experiences of the Maryland Department of Transportation with SMA as well as referring to a recently produced report titled Construction and Performance of Stone Matrix Asphalt Pavements in Maryland: An Update.

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)0.002
metaresearch head score (Gemma)0.002
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.068
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0680.017

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 head0.030
GPT teacher head0.264
Teacher spread0.234 · 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
GenreOther

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

Citations0
Published2002
Admission routes1
Has abstractyes

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Same venueHMAT: Hot Mix Asphalt TechnologySame topicAsphalt Pavement Performance EvaluationFrench-language works237,207