SAMPLE III SC.02 - Studying, sAmpling and Measuring of aircraft ParticuLate Emissions III: Specific Contract 02
Bibliographic record
Abstract
The main objective of the SAMPLE III framework contract is to contribute to the development of aircraft engine particulate matter certification requirements and standards.During the last six years EASA funded the so called SAMPLE project that contributed to the development of a sampling and measurement method for non-volatile particulate matter at the exhaust of aircraft engines and helped to draft the corresponding AIR6241 that was issued in November 2013.A first task of this specific contract was to collaborate to the writing of the ARP based on the AIR6241 and using the technical knowledge gained from the current and past studies. This ARP will be the basis for the drafting of technical requirements in ICAO Annex 16, Vol.II.Secondly, measurements were carried out at the exhaust of Rolls-Royce aircraft engines simultaneously with the EASA and Rolls-Royce nvPM systems for comparison. The data obtained will be used to start to fill in the nvPM data base for the setting of future ICAO mass and number nvPM standards.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.014 |
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".