Toward New Frontiers in Understanding the Link Between Dust and Climate; DUSTSPEC Workshop: Dust Records for a Changing World; Palisades, New York, 24–26 May 2010
Bibliographic record
Abstract
Mineral dust is an active climate system component that may significantly influence the radiative balance of the atmosphere as well as biogeochemical cycles. However, the complex linkages between dust‐generating processes and past or anthropogenic climate change are still poorly constrained. The highly successful Dust Indicators and Records of Terrestrial and Marine Palaeoenvironments ( DIRTMAP) project, created by Karen Kohfeld (Simon Fraser University, Burnaby, British Columbia, Canada) and Sandy Harrison (University of Bristol, Bristol, United Kingdom) in 2001, provided a compilation of available dust deposition data from climate archives. DIRTMAP focused on a time slice approach, compiling data for modern/ Holocene (up to ∼10,000 years ago to the present) conditions and conditions at the Last Glacial Maximum (∼20,000 years ago).
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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".