Bibliographic record
Abstract
Measurements were made in 2 sets of cold air outbreaks using the UK FAAM BAE 146 research aircraft. The first set were performed in March 2022 over the Eastern Atlantic the second set were perform in October to early November 2022 in the Western Atlantic over the Labrador Sea based in Goose Bay, Eastern Canada. In each set of experiments the focus was to study the evolution of the cloud microphysics as influenced by Cloud condensation nuclei, ice nuclei and secondary ice processes in the stratocumulus clouds being advected southwards over progressively warmer sea until cloud break-up occurred into convective clouds. The aims were to improve the treatment of these cloud types in Global climate models and weather forecast models. These projects formed part of m-Phase funded by NERC as part of its Cloud Sense programme and ACAO a Met office program to study these clouds.A range of aerosol and cloud microphysical equipment was used in the 2 projects which will be discussed in the presentation.Analysis of the data set including a new novel Holographic instrument is still underway at the time of writing; however, some preliminary results indicate that: Generally the ice crystal number concentration exceeded the ice nucleus concentrations measured at the same temperature Some regions consisted entirely of super cooled water A range of secondary ice particle production mechanisms were observed including ice splinter production during riming and droplet shattering on freezing after capture by ice crystals Generally if the convective region was reached by the aircraft then secondary ice production was greater than in the stratocumulus region Precipitation was mostly in the ice phase
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".