Demonstration and validation of an environmentally compliant vinyl coating system for cold locations
Bibliographic record
Abstract
Cold-weather paint application to prevent corrosion of steel structures is expensive because it usually requires the construction of heated containment structures to ensure successful results.The Corps of Engineers V-776e solution vinyl paint formulation can be applied at low temperatures, but its volatile organic compound (VOC) content exceeds regulatory maximum level, so permissible applications of it are highly restricted.This report documents the demonstration and validation of a new low-VOC solution vinyl coating material that is based on the Corps of Engineers V-766e formulation.This material, called formulation V-766-LVOC, meets the regulatory VOC limit and can be applied to steel structures in low temperatures without heated containment.The demonstration coating was applied to a Bailey-type bridge on the Yukon Training Range at Fort Wainwright, AK.The corrosion performance and applicability results were considered to be comparable to the restricted V776e formulation, and application operation costs were lower than those for a conventional oil/alkyd formulation that would require heated containment.The return on investment (ROI) for this technology, including demonstration project management costs, was calculated to be 0.6; in a real-world project that includes only paint materials and application costs, the ROI becomes 2.85.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".