Bibliographic record
Abstract
Flight research of the characteristics of trailing vortices, generated by heavy jet transport aircraft in cruising flight, was conducted. Trailing vortex velocities were derived by vectorial differencing of aircraft inertial velocity and true airspeed vectors, and then transforming to the vortex mean axis. Lateral distances between port and starboard vortices were 60–70% of generator wingspan. Vortex core radii were derived. Core pressure states were expanded or diffused. Core diffusion was associated with axial segmentation. Core pressure expansions included magnitudes greater than Euler equilibrium values, with velocity profiles displaying peaked maxima. Associated with these characteristics was vortex core radial instability. Subsequent radial expansion and contraction resulted in a large range of rC values. Vorticity confined to an annular state and discretized into circular arrays of N-point vortices of small rC was prevalent. Radial profiles of vortex velocity were identified and included Rankine (peaked) profiles, Lamb-Oseen, and Burnham-Hallock rounded profiles. Twenty-five percent of identified profiles were rounded. The majority of profiles were peaked, with maxima greater than, or equal to, Rankine values. Temperature gradients inside and outside of core edges were identified: outside, heating occurred, inside, cooling. Outer heating occurred with upstream axial flow. Inner cooling occurred with downstream axial flow.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".