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Record W4235014808 · doi:10.1201/9781315119205-2

Standards

2017· book-chapter· en· W4235014808 on OpenAlexaboutno aff
Rajib B. Mallick, Tahar El‐Korchi

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Standards are documents provided by expert and recognized organizations, which provide guidelines or characteristics of common activities to ensure consistency, quality, and safety. Standards are developed on the basis of research and experience through consensus of groups of experts. Generally, standards used in pavement engineering are those that are developed by traditional formal organizations such as the American Society for Testing and Materials (ASTM International), the American Association of State and Highway Transportation Officials (AASHTO), the Asphalt Institute, the American Concrete Institute (ACT), and the British Standards Institution (BSI). AASHTO standards are developed either separately or, if appropriate, on the basis of existing ASTM standards by the AASHTO Highway Subcommittee of Materials, with representatives of transportation department officials in the United States, associate members, and international members, such as those from the Canadian provinces and Korea.

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)0.007
metaresearch head score (Gemma)0.022
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: Methods · Consensus signal: none
Teacher disagreement score0.178
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.006
Science and technology studies0.0030.002
Scholarly communication0.0080.007
Open science0.0050.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.1780.189

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 head0.024
GPT teacher head0.268
Teacher spread0.244 · 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
GenreMethods

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
Published2017
Admission routes1
Has abstractyes

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