Protocol for Selecting ASR-Affected Structures for Lithium Treatment
Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.103 | 0.036 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".