Mineral Dust and Climate: Working Group on Dust and Climate Joint INQUA/QUEST Workshop; Villefranche‐sur‐Mer, France, 19–22 October 2008
Bibliographic record
Abstract
Mineral aerosol (referred to here as “dust”) is an active climate and paleoclimate system component that may significantly influence the radiative properties of the atmosphere, as well as ocean and atmospheric carbon dioxide (CO2) concentrations, through processes such as iron fertilization. The integrative, cross‐cutting examination of the role and significance of dust provides the rationale for the Dust Indicators and Records of Terrestrial and Marine Paleoenvironments (DIRTMAP) working group sponsored by the International Union of Quaternary Research and the Natural Environment Research Council's Quantifying and Understanding the Earth System (QUEST) program. The working group aims to initiate coordinated progress to improve the representation of dust properties in dust cycle models, with particular focus on dust mineralogy, such as the concentrations of iron oxides and oxyhydroxides as either nanoparticles or mineral coatings, and particle size distribution. These two sets of factors are potentially significant in assessing the effects of dust on both radiative forcing and biogeochemical cycling. The working group also aims to improve model simulation of dust source regions, the episodic nature of dust emissions, and amounts of dust deposition over the continents.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.046 | 0.012 |
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".