Particle fluxes and condensational uptake over sea ice during COBRA
Bibliographic record
Abstract
Particle fluxes were measured over sea ice at Hudson Bay, Canada, during the COBRA experiment in February and March, 2008. Eddy covariance particle fluxes were measured using a condensation particle counter and an ultrasonic anemometer on a 2.5 m mast on the sea ice. After applying appropriate corrections and filtering, the mean net deposition velocity was 0.12 ± 0.11 mm s−1 for particles measured with a CPC 3776 (lower size threshold, Dp50 = 2.5 nm) and was at the detection limit of the measurement system. No evidence of nucleation events was seen. Two optical particle counters (at heights 0.2 and 1.35 m on the mast) allowed size segregated fluxes of particles in the accumulation and coarse mode diameter range 0.3–20 μm to be derived using the aerodynamic flux gradient method. Strong net emission fluxes were observed around midday, 3rd March, when winds increased to around 10 m s−1, suggesting ice particle resuspension. The fluxes during this period had a significant influence on the derived condensational loss rate to the available particle surfaces, kt. Number fluxes were greatest in the smallest size channels, while the largest sizes dominated the mass flux. Number fluxes also increased with wind speed, and this relationship was strongest for the smaller sizes. Particle mass size distributions showed an enhanced mode around 400 nm (dry size). Values of kt were well approximated by the molecular regime and were found to be much smaller and less variable than values derived for marine air.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".