On the Identification and Characterization of Drought and Aridity in Postglacial Paleoenvironmental Records from the Northern Great Plains
Bibliographic record
Abstract
The Northern Great Plains region is especially sensitive to drought and is likely to be even more drought-prone under projected global warming. Drought has been invoked as an explanatory factor for changes seen in postglacial paleoenvironmental records. These proxy records may extend drought history derived from instrumental data. Moreover, in the last decade, some paleoenvironmental studies have been expressly undertaken for the examination of long-term drought history. Nevertheless, few such studies explicitly define drought. This makes it difficult to compare results or to understand what the results mean in terms of the operational drought definitions that are used in resource management. Operational drought is defined as usually short-term; longer sustained dry intervals reflect a shift to aridity. Therefore, high resolution paleoenvironmental proxies (annual or subdecadal) are best for the investigation of drought history. Such proxies include tree rings and some lake records. However, most lake-based records are sampled at lower resolution (decadal or subcentury) and are therefore providing aridity signals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".