A practical investigation of a takeoff performance monitor for turboprop aircraft
Bibliographic record
Abstract
The purpose of an aircraft Takeoff Performance Monitoring System (TOPMS) is to provide to the pilot information pertaining to the level of safety with which a takeoff is proceeding. The concept of a TOPMS is not new. Instruments have been developed and flight tested, however the inclusion of a TOPMS as a standard instrument has yet to be embraced by manufacturers and operators. The authors have investigated the feasibility of using an observer system during the roll and takeoff phase of aircraft operation to provide to the pilot the information that is needed to manoeuver safely. Unlike previous work in this field, this investigation focussed on various factors that are unique to the far-northern environment. Further, the Global Positioning System(GPS) was proposed as the sole source of kinematic information. This provided the possibility that a TOPMS could be devised that would require no additional ground-based installation. A theoretical dynamic model of an aircraft in contact with the ground appears in AIAA 2001-4374, together with an uncertainty analysis and a description of the signal processing technique. A GPS receiver and data acquisition system were installed in an aircraft
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".