Chemical characterization of individual particles and residuals of cloud droplets and ice crystals collected on board research aircraft in the ISDAC 2008 study
Bibliographic record
Abstract
Ambient particles and the dry residuals of mixed‐phase cloud droplets and ice crystals were collected during the Indirect and Semi‐Direct Aerosol Campaign (ISDAC) near Barrow, Alaska, in spring of 2008. The collected particles were analyzed using Computer Controlled Scanning Electron Microscopy with Energy Dispersive X‐ray analysis and Scanning Transmission X‐ray Microscopy coupled with Near Edge X‐ray Absorption Fine Structure spectroscopy to identify physico‐chemical properties that differentiate cloud‐nucleating particles from the total aerosol population. A wide range of individually mixed components was identified in the ambient particles and residuals including organic carbon compounds, inorganics, carbonates, and black carbon. Our results show that cloud droplet residuals differ from the ambient particles in both size and composition, suggesting that both properties may impact the cloud‐nucleating ability of aerosols in mixed‐phase clouds. The percentage of residual particles which contained carbonates (47%) was almost four times higher than those in ambient samples. Residual populations were also enhanced in sea salt and black carbon and reduced in organic compounds relative to the ambient particles. Further, our measurements suggest that chemical processing of aerosols may improve their cloud‐nucleating ability. Comparison of results for various time periods within ISDAC suggests that the number and composition of cloud‐nucleating particles over Alaska can be influenced by episodic events bringing aerosols from both the local vicinity and as far away as Siberia.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".