Bibliographic record
Abstract
A quasi-physical model (having both physical and mathematical roots) of sprint performances is presented, accounting for the influence of drag modification via wind and altitude variations.The race-time corrections for world class male sprinters are discussed, and theoretical estimates for the associated drag areas are presented. The corrections are consistent with constant-wind estimates of previous authors. At sea level, world class men's race times are adjusted by about 0.10 s for a wind speed w = 2 m s-1, while every 1000 m of altitude provides an advantage of roughly 0.030.04 s. Corrections are provided for a wide range of wind speeds (-5 to +5 m s-1) and altitudes (02500 m), as well as for variable winds whose time-averaged value does not realistically reflect the ambient conditions. A simplified algebraic expression is also presented to correct 100 m sprint times for ambient wind and altitude effects. The primary aim is to demonstrate the utility and robustness of the full model in making such predictions, after which accurate measurement of each parameter can help to fine-tune these results. As a practical example of its utility, the nullified World Record and 1988 Olympic 100 m race of Ben Johnson is studied, and compared with the present World Record of 9.79 s. PACS Nos.: 01.80, 02.60L
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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".