PCSAIL, A Velocity Prediction Program for a Home Computer
Bibliographic record
Abstract
An Excel Velocity Prediction Program has been developed to allow for rapid evaluation of yacht performance at the initial design stage. The required input consists of only the basic hull and sail dimensions. Empirical equations, based on these basic dimensions, are used for initial estimates of required hull parameters. As the design progresses the user can easily replace these default values with refined estimates or actual values. Because of its simplicity, and short turn around time, the program has been used as a teaching aid at the University of Michigan. Reconstruction of the program, PCSAIL, may be made with equations and other information provided in the Appendix. The Excel "Solver" has been found to be a reliable means of finding the equilibrium boat speed and heel angle. It seeks the maximum boat speed by adjusting the sail flattening factor, F, and reef, R, and the lateral location of the "movable crew." In the case of a hinged centerboard, or dagger- board, it will also adjust the draft for maximum boat speed. For sloop rigs the program will also take in the jib and set the spinnaker, at the appropriate wind angle, in order to gain maximum boat speed. The program plots the speed "polar," and velocity made-good, and determines the tacking angles.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.116 | 0.051 |
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".