Design of a yaw restraining heave post
Bibliographic record
Abstract
The Institute for Ocean Technology is a national research facility that specializes in the testing of scale models. In many cases they are models of vessels that may one day see production. The information gathered from the testing facilities will give the people who designed the vessel a sense of how the vessel will perform in the real world. Often the models are not self propelled, yet propulsion must come from the carriages above the tow tanks. Often the propulsion is transferred to the models through the use of a heave post. The current heave post does not have the ability to restrict the motion of the model about its own axis. Therefore another piece of equipment is used to accomplish this task. There are a number of problems associated with this device that are considered undesirable. To eliminate the use of this piece of equipment a new heave post was designed. In order to have a heave post which functioned properly a set of design criteria were established. The design criteria lead to the development of several designs, from which the best suited candidate was chosen. The new heave post, when it is manufactured will supplement the existing heave post, giving the facility the ability to operate more smoothly.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".