Buoyancy-Corrected Gravimetric Analysis of Lightly Loaded Filters
Bibliographic record
Abstract
Numerous sources of uncertainty are associated with the gravimetric analysis of lightly loaded air filter samples (< 100 microg). The purpose of the study presented here is to investigate the effectiveness and limitations of air buoyancy corrections over experimentally adjusted conditions of temperature (21-25 degrees C) and relative humidity (RH) (16-60% RH). Conditioning (24 hr) and weighing were performed inside the Archimedes M3 environmentally controlled chamber. The measurements were performed using 20 size-fractionated samples of resuspended house dust loaded onto Teflo (PTFE) filters using a Micro-Orifice Uniform Deposit Impactor representing a wide range of mass loading (7.2-3130 microg) and cut sizes (0.056-9.9 microm). By maintaining tight controls on humidity (within 0.5% RH of control setting) throughout pre- and postweighing at each stepwise increase in RH, it was possible to quantify error due to water absorption: 45% of the total mass change due to water absorption occurred between 16 and 50% RH, and 55% occurred between 50 and 60% RH. The buoyancy corrections ranged from -3.5 to +5.8 microg in magnitude and improved relative standard deviation (RSD) from 21.3% (uncorrected) to 5.6% (corrected) for a 7.2 microg sample. It is recommended that protocols for weighing low-mass particle samples (e.g., nanoparticle samples) should include buoyancy corrections and tight temperature/humidity controls. In some cases, conditioning times longer than 24 hr may be warranted.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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, unvalidatedMachine predicted; a candidate call from one teacher head, 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".