Bibliographic record
Abstract
The March 2010 issue of The Physics Teacher includes a great article by Metz and Stinner on the kinematics and dynamics of a space shuttle launch.1 Within those pages is a brief mention of an event known in the language of the National Aeronautics and Space Administration (NASA) as “maximum dynamic pressure” (called simply “Max.AirPressure” in the article), where the combined effect of air density and the shuttles speed produce the greatest aerodynamic stress on the vehicle as it ascends through the atmosphere toward orbit. Official commentary during a launch2 refers to this point in the ascent with language such as “space shuttle main engines throttling back as vehicle enters area of maximum dynamic pressure” and occurs in a range between 45 and 60 s after launch. (In dealing with this stress, the space shuttles main engines reduce their thrust at approximately 45 s to reduce acceleration, and return to normal levels again some 15 s later as maximum dynamic pressure is traversed.) This paper presents an analysis, accessible to introductory-level students, that predicts the time of Max. AirPressure for a given ascending spacecraft.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.005 | 0.001 |
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".