Advances in service life prediction - an overview of durability and methods of service life prediction for non-structural building components
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
An overview is provided of durability, service life (SL) and service life prediction (SLP) research in the construction domain over the past decades with emphasis on the activities of the CIB W080 working commission and related RILEM technical committees working in this area. The information serves as a primer on the topic and offers useful references on SL and SLP methods for the principal building components such as wood, sealants, coatings, roofing, and rendered cladding. As well, the SL methods developed for more complex construction components, such as insulated glass units and solar collectors, are summarised and serve to illustrate the approaches taken when estimating the SL of multifaceted building assemblies. A key component to SLP research within the CIB W080 has been interest in making the outgrowth of the research accessible to the practitioner. As such the dissemination of SL information in the form of building codes and standards are addressed and the prominence of information technologies, such as the Internet, in facilitating the dissemination process is also touched upon. Finally, examples reflecting current trends in SLP are presented and expectations for future research focus are offered.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it