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Record W7070843969

Protocol for Selecting ASR-Affected Structures for Lithium Treatment

2004· other· en· W7070843969 on OpenAlexaboutno aff

Bibliographic record

VenueRosa P: A digital library for transportation research (United States Department of Transportation) · 2004
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionHyporeflexiaTSG101DiafiltrationGestational periodSubpoenaFusible alloy
DOInot available

Abstract

fetched live from OpenAlex

This document describes a protocol for evaluating damaged structures to determine whether they are suitable candidates for lithium treatment to address alkali-silica reaction (ASR). A major part of this report deals with the approach/tools that can be used to determine whether ASR is the principal cause or only a contributing factor to the observed deterioration (diagnosis), determine the extent of deterioration due to ASR in the structure, and evaluate the potential for future expansion due to ASR (prognosis). Finally, the report lists items to be included in the proposal that will be submitted for the selection of structures for lithium treatment.\nGuidelines on evaluating and managing structures affected by ASR have been published by the Canadian Standards Association (CSA).(1) Pictures of field symptoms and petrographic features of ASR can be found in the documents from CSA, the British Cement Association, the American Concrete Institute, Stark, and Farny and Kosmatka. (See references 1, 2, 3, 4, and 5.) More recently, Folliard and Kurtis summarized such features as part of the Federal Highway Administration (FHWA) workshop material "Guidelines for the Use of Lithium to Mitigate or Prevent ASR in Concrete."\n

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.134
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.050
GPT teacher head0.351
Teacher spread0.301 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueRosa P: A digital library for transportation research (United States Department of Transportation)French-language works237,207