Bibliographic record
Abstract
One of the most impressive features of the new Tacoma Narrows Suspension Bridge is something that few people ever notice--the two large caissons that support the bridge. This article describes the design and construction of the caissons. The caissons are two of the largest and deepest in the world, planted nearly 200 feet below the surface. Although caissons are considered older and more expensive than other foundation technology such as drilled shafts, the engineers felt that the caissons represented the best foundation for the seismic-prone Puget Sound. State-of-the art, three-dimensional computer models were used to predict how the caissons would respond throughout the course of potential seismic events. Each caisson's footprint is 80 ft by 130 ft. The structures are designed to withstand average 7-knot, 15-foot tidal swings and a 50-ft scour potential, as well as seismicity capable of producing earthquakes of 8 or larger on the Richter scale. The caissons were constructed in three parts and took about 18 months from design to completion. This project highlights the importance of conducting a thorough engineering analysis and keeping an open mind when choosing the best design features for a challenging project.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.218 | 0.102 |
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".