Laboratory studies of ice formation via deposition mode nucleation onto mineral dust and n‐hexane soot samples
Bibliographic record
Abstract
Laboratory studies are described whereby the heterogeneous ice nucleating ability of various dust samples was studied for particles mounted on a hydrophobic cold stage. Ice formation is observed using digital photography. The relative humidity with respect to ice (RHi) and temperature conditions of the flow system are validated by observing (NH4)2SO4 deliquescence. Four types of solid mineral samples, including authentic Saharan dust and commercial samples of alumina, silica, and montmorillonite, were investigated in the deposition freezing mode. The size of the dust particles ranged from 0.5 to 5 μm, and the temperature range was from 263 to 218 K. With roughly 104 particles present on the cold stage, the onset for ice formation was observed at low RHs, between 102 and 108% RHi, for all samples and temperatures. This indicates that deposition mode nucleation is an efficient mode of ice formation, particularly under the cold temperatures prevalent in the cirrus regime. By contrast, ice deposition onto n‐hexane soot particles was not nearly so efficient. Nucleation rates are calculated as a function of RHi from experiments conducted with Saharan dust, where we measured the dependence of the onset RHi on total dust surface area.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".