Engineering lessons from the 28 September 2018 Indonesian tsunami: debris loading
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
A field survey team went to Palu City, Indonesia in the aftermath of the September 28th, 2018 earthquake and tsunami to investigate its effects on local infrastructure and buildings. The study focused on the coast of Palu Bay, where a tsunami wave between approximately 2 and 7 m high impacted the local community as a result of several complex tsunami source mechanisms. The following study outlines the results, focused on loading caused by debris entrained within the inundating flow. Damage to timber buildings along the coast was widespread, though reinforced concrete structures for the most part survived, providing valuable insights into the type of debris loads and their effects on structures. The results of this survey are placed within the context of Canadian tsunami engineering challenges and are compared to the recently-released ASCE 7 Chapter 6 – Tsunami Loads and Effects, detailing potential research gaps and needs.
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 | 0.001 |
| 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 it