Automated Weighing of PM Filters: Impact of Equilibration Duration
Bibliographic record
Abstract
This study aims to present results from the repeated measurements of unloaded PM filter mass using the robotic weighing system RB 2.4Y.F, (Radwag, Poland) and to select the most appropriate equilibration time.The criteria for filter equilibration used in this study followed the PN-EN 12341:2024 standard.For that purpose filters of different types (quartz-QF, glass-GF, nylon-N, Teflon-PTFE, and polycarbonate-PC) were equilibrated in a controlled atmosphere, and weighed in replicates for nearly two weeks in the case of quartz fibre filters and for over a month in case of other filters to check the effect of conditioning time on filters mass deviations.This study aimed to compare mass deviations among filters along with increasing conditioning time and, consequently, determine the choice among acceptable filters based on mass stabilization criteria.As a standard, 9 successive filter weighing cycles were performed, except for quartz filters for which 3 weighing cycles were carried out.Based on the obtained results, the average mass of the unloaded quartz filters remains stable throughout the conditioning time while maintaining constant relative humidity (50 ± 5%) and air temperature (20 ± 1°C).Similar results were observed in the case of glass fibre filters.The weight of Teflon and polycarbonate filters stabilized much longer (in the 4th and 6th weighing cycles, respectively), and it was higher by more than 1 mg than the initial weighing.The reason for the longer stabilization time compared to quartz or glass fibre filters was most likely the absorption of electrostatic charges on the surface of Teflon and polycarbonate filters, caused by the ineffective operation of the deionization gate.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".