Bibliographic record
Abstract
Achieving long term durability and sustainability in the built environment is one of the principal construction targets of governments around the world. A limiting factor to durability in reinforced concrete structures is corrosion of the steel reinforcement, and structures exposed to coastal environments and/or subject to the application of de-icing salts, are particularly susceptible to damaging chloride ions from these sources. The consequence of corrosion is more frequent repair or a reduction in the design life. Corrosion damage world-wide has been estimated in billions of US dollars. Stainless steel reinforcement can provide the durability commensurate with the design life of the structure. It has been approved for use in highway bridges by the UK Highways Agency, the Federal Highways Administration in the USA, Ministry of Transportation in Canada, and Scandinavian Road Authorities. New British and USA Standards for stainless steel rebar have been issued, and guidance on the application of stainless steel rebar was issued by the Highways Agency in their Design Manual for Roads and Bridges in 2002. This paper will discuss the new documentation outlined and illustrate that increased durability can be obtained using stainless steel reinforcement for only a small increase in capital cost. Whole life costs will be shown to offer significant cost savings. INTRODUCTION BS6744:2001 STAINLESS STEEL BARS FOR THE REINFORCEMENT OF AND USE IN CONCRETE [5] HIGHWAYS AGENCY GUIDELINES BA84/02 [6] INITIAL AND WHOLE LIFE COSTS CONCLUSIONS REFERENCES
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.039 | 0.028 |
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".