Bibliographic record
Abstract
While all the major NATO navies have been under considerable pressure to downsize following the end of the post-Cold War, the higher degree of political instability world-wide has led to a desire to increase the deployability of the reduced number of naval assets. Thus there has been an increased interest in providing a new generation of naval support vessels as part of each navy’s contribution to Coalition peacekeeping. These new support ships are often also required to provide a contribution to amphibious capabilities, including humanitarian tasks, in littoral operations. This means there is a challenging combination of capabilities being sought from the current replacements of traditional afloat support ships. This paper describes the design work undertaken by the Design Research Centre at UCL, as part of a bid team responding to a Canadian National Defence Department requirement for feasibility studies into a “Joint Support Ship” programme. The UCL task consisted of designing a range of possible design options, to investigate the impact of capabilities on the configuration of this innovative concept, exploring the requirement’s two levels of capability, namely, “shall” and “should” as part of designing to cost and capability. A range of concepts was designed using the UCL Design Building Block approach, using the SURFCON module of the Graphics Research Corporation PARAMARINE ship design system. The advantage this approach gave in designing these novel solutions is shown through the ability of the DBB concept approach to balance both technical and configurational features, thereby enabling significantly different ship styles to be readily produced and compared.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".