Mineral aerosols: a comparison of the last glacial maximum and preindustrial Holocene
Bibliographic record
Abstract
A passive mineral dust aerosol model based on source strengths deduced from polar ice core dust concentrations is introduced into the Canadian Centre for Climate Modelling and Analysis (CCCma) second-generation atmospheric general circulation model (GCMII) and used to compare features of the fine particle mineral dust aerosol in a last glacial maximum (LGM) simulation to those of a preindustrial Holocene (MOD) dust simulation. The resulting dust optical thickness is 8-16 times greater over most of the globe during the LGM. The model displays several seasonal characteristics observed in present-day satellite observations of dust, such as the summer maximum over the Arabian Sea and the seasonal north-south shift of the Sahara-Sahel plume. Both of these features are also present in the LGM simulation, though there are some noticeable differences in seasonal variation of dust between the last glacial maximum and the preindustrial Holocene. Since the simulated dust lifetimes are very similar for the MOD and LGM climates, it seems that increased LGM dust lifetime is not the major reason for the observed increase in dust concentration in polar ice cores during the LGM relative to the present.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".