Bibliographic record
Abstract
About four decades ago the offshore industry began in earnest to seek and develop energy resources in particularly harsh marine environments, such as the North Sea, which is visited frequently by severe extratropical cyclones, and the Gulf of Mexico, in which intense tropical cyclones may occur in any given year. With the discovery of the giant Hibernia oil field offshore Newfoundland in the mid-1970s and other finds offshore Nova Scotia soon thereafter, the need for high quality design Metocean data as required for the reliable, safe and cost effective design of offshore infrastructure extended to these areas as well. The socalled hindcast approach emerged during these relatively early years as the only reliable method available to specify Metocean design data in a rational and objective way. The hindcast approach consists of the application of numerical wind and wave models together with historical meteorological data to simulate the evolution of surface winds and ocean wave response in the basin or region of interest. Application of the statistical process of extremal analysis to the hindcast data at specific sites yields the design criteria (e.g. 100-year return period significant wave height) required by structural engineers.
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 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".