A heuristic solution for the stability problem in conventional submarines
Bibliographic record
Abstract
Seafaring vessels must meet a few very obvious conditions in order to be of any use. The one condition is that they should stay afloat when loaded. The other condition is that they should float upright and with a level keel. The technical terms for these conditions are gravitational stability and trim. In practice some very precise numerical values are calculated for certain parameters in order to describe these conditions. After each refit of a submarine, the numerical values for the parameters referred to above must be recalculated. In the conventional submarines used by the South African Navy these new values must then be translated into the physical redistribution of weights housed in bays in the keel of the submarine. This paper discusses the problem of how this redistribution must be done in order to minimise the amount of work necessary. A heuristic algorithm is proposed by means of which a satisfactory redistribution may economically be computed.
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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 | 0.001 | 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".