Quantitative capabilities of STXM to measure spatially resolved organic volume fractions of mixed organic/inorganic particle
Bibliographic record
Abstract
Abstract. Scanning Transmission X-ray Microscopy coupled with Near-Edge X-ray Absorption and Fine Structure (STXM/NEXAFS) spectroscopy can be used to characterize the morphology and composition of aerosol particles. Here, two inorganic/organic systems are used to validate the determination of Organic Volume Fraction (OVF) from STXM data and to determine the level of associated error. Using the mixture of sodium chloride and sucrose as one system and ammonium sulfate and sucrose as another, three solutions each were made with 10:1, 1:1, and 1:10 mass ratios (inorganic to organic). The OVF of the organic rich aerosols of both systems deviated from the bulk OVF by less than 1 %, while the inorganic rich aerosols deviated by approximately 1 %. Aerosols from the equal mass mixture deviated more (about 4 %) due to thick inorganic regions exceeding the linear range of Beer’s Law. These calculations were performed after checking the data for image alignment, defocusing issues, and particles too thick to be analyzed. The potential for systematic error in the OVF calculation was also tested by assuming the incorrect composition. There is a small (about 0.5 %) OVF difference if adipic acid is assumed rather than sucrose, and a much larger (up to 25 %) difference if sodium chloride is assumed instead of ammonium sulfate. These results show that, with attention paid to ensuring quality data, an OVF value within 1 % of the theoretical value can be determined.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".