Evaporative Leakage from Gas Caps
Bibliographic record
Abstract
The AirCare® vehicle emissions inspection and maintenance program is briefly described, together with the benefits which the program has already achieved. Additional benefits have been projected should the program include some more sophisticated assessment of evaporative emission control systems. The feasibility of including such an assessment has been investigated, and a pilot study has been conducted in the regular inspection lanes. The operational and systems implications are described. The pilot study has resulted in an analysis of the incidence of faulty gas caps in the Lower Fraser Valley light-duty vehicle fleet, and how this relates to other vehicle characteristics such as vehicle make, model, model year, mileage etc.; and inspection data including emission control system components tampering and tailpipe emissions. Approximately 10% of all gas caps tested failed the pressure test, compared to the 1% that were failed by visual inspection. Correlation with other vehicle and inspection data showed that the likelihood of a leaking gas cap cannot be accurately predicted without a functional test. The second part of this paper describes the operation, construction and testing results of a Gas Cap Leakage Rate Tester. The Leakage Rate Tester is capable of precisely measuring the mass flow rate out of a leaking gas cap at specific pressures. Over 170 fuel caps were tested on this unit and results separated into three groups; those that fail the EPA Pressure Test, those that passed, and anomalous Honda fuel caps. These results are analysed as a precursor to larger-scale fleet projections. This work has formed the first and second parts of a more comprehensive evaporative emissions assessment and modelling project.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".