Quantification of the repeatability and reproducibility of the CPMA-electrometer reference mass standard for in-situ calibration of mass concentration aerosol instruments
Bibliographic record
Abstract
Mass-concentration aerosol instruments require frequent calibration to provide precise and accurate measurements. Such calibrations for mass instruments can be achieved with the Centrifugal Particle Mass Analyzer (CPMA)–Electrometer Reference Mass Standard (CERMS). This study presents an interlaboratory comparison of CERMS and its two major components: the Faraday Cup Aerosol Electrometer (FCAE) and CPMA. The CERMS repeatability and reproducibility, defined as measurement precision under repeatable and reproducible measurement conditions, are evaluated. Our study was conducted in two phases: laboratory and field studies, and involved three independent laboratories. In the laboratory study, comparisons were made using soot and size-selected dioctyl sebacate (DOS) particles, using a transfer instrument. In the field, nebulized ammonium sulfate and soot from two turbine engine source exhausts, including a J85 turbojet engine, were used to compare the CERMS systems using three transfer instruments. Results indicated that the FCAEs exhibited excellent repeatability and reproducibility (<2%), while the CPMAs showed excellent repeatability (<3%) but poorer reproducibility (about 10%) due to instrument biases. In the laboratory study, the entire CERMS system demonstrated low uncertainty under repeatable conditions (3%) but higher uncertainty under reproducible conditions (∼11%). Field study uncertainties for CERMS were larger than in the laboratory (repeatability ∼8%, reproducibility ∼11%), likely due to the combined uncertainties from the transfer instruments, particle sources, CERMS components, and the less-controlled environment. Since biases between CPMAs were the major contributor to overall CERMS reproducibility, CPMA calibration could provide a significant improvement to CERMS reproducibility.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".