PROCEEDINGS of the International Conference on Transport and Environment: A Global Challenge Technological and Policy Solutions, Milan, Italy, 19-21 March 2007. SESSION D: Advanced Particle Emission Measurements and Abatement
Bibliographic record
Abstract
The increasing evidence of the health effects attributed to particles generated in internal combustion engines has led several governments to investigate new and advanced methods to measure such particles. Such investigations have been carried out during the past years within the UN-ECE GRPE Particulate Measurement Programme (PMP), where UK, Germany, France, Sweden, Switzerland, Greece, Japan and Korea have participated, while other similar investigations have gone ahead in the US.\nThe PMP has now completed its validation programme for the method designed for\nmeasuring the number of particles emitted by light-duty vehicles and is about to start the validation programme for the testing procedure related to heavy-duty engines. The results of this programme were already referred to in the upcoming EURO-5 legislation and similar interest has been shown for inclusion in the EURO-VI legislation. At the same time there has been increasing interest to participate in the programme throughout the world with other countries recently joining.\nThe scope of the session was:\n• To compare results of the LD PMP interlab exercise (2003-2006),\n• To present the result of other investigations such as the Swiss and CARB PMPlike\nprogrammes\n• To stimulate the exchange of information and views between the different\napproaches for PM emission measurement;\n• To discuss the latest technological and regulatory developments regarding\nmeasurements of PM;\n• To define the programme for the HD-PMP Interlab exercise (with probable worldwide\nparticipation, EU, USA, Canada etc..)\nTopics:\n• PMP LD interlaboratory validation exercise and other similar investigations\n(AECC, Swiss, CARB, etc…), lessons learned, further investigations needed,\nproblems and solutions, etc.\n• Kick-off for the PMP HD interlaboratory validation exercise, participation of other\nlabs, presentation of golden measurement system, discussion on the time-table\n• Instruments for PM emission measurements, validation, calibration, new\ntechniques, etc.\n• Devices for abatement of particles, PM traps, etc.\n• Legislation for the abatement of PM from vehicles in Europe and the world.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.151 | 0.055 |
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".