Sustainability of Infrastructures vs. Climate Changes
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
<p> Climate changes became a challenge for the sustainability of infrastructures which are expected to perform during long life-cycles. However, “the forces of mother nature” reflected in codes; do not always cover caprices of the nature manifested in extreme weather events such as abundant snow falls, heavy winds, freezing rain, flooding, etc…..which never occurred before. Examples from Quebec where generally snow falls are important, a “great” ice storm occurred in 1998 and heavy rains became a frequent phenomenon; can serve as examples for the behaviour of some infrastructures in unusual weather conditions. The character and the range of failures caused by snow, wind, ice build-up, etc… in regions regularly exposed to these loads, can serve as a reference for the performance of structures elsewhere, where hazards form climate changes; Forensic Engineering deals with such issues. A parallel between “poorly” designed structures and effects of climate changes leads to the conclusion that quality of design remains the main issue in the consideration regarding these aspects.</p>
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