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 full-scale field experiment is an important part in the design of ships and offshore structures. Full-scale tests in the ice-covered sea, however, are usually very expensive and difficult tasks. Model tests in a refrigerated ice tank may substitute this difficulty of full-scale field tests. One of the major tasks to perform proper maid tests in an ice towing tank is to select a realistic material for model ice which shows correct similitude with natural sea ice. This study focuses. on the testing material properties and the selection of model ice material which well be used in an ice model basin. The first Korean ice model basin will be constructed at the Maritime & Ocean Engineering Research Institute(MOERI) in 2009. With an application to the MOERI ice model basin, in this study the material properties of EG/AD/S model ice of IOT(Institute for Ocean Technology) Canada, were tested. Through comprehensive bending tests, the elastic modulus and the flexural strength of EG/AD/S model ice were evaluated and the results were compared with published test results from Canada. Instead of using an ice model basin, a cold room facility was used for making a model ice specimen. Since the cold room adopts a different freezing procedure to make model ice, the strength of the model ice specimen differs from the published test results. The reason for this difference is discussed and the future development for a making model ice is recommended.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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