Diatom-inferred changes in effective moisture during the late Holocene from nearshore cores in the southeastern region of the Winnipeg River Drainage Basin (Canada)
Bibliographic record
Abstract
The Winnipeg River Drainage Basin (WRDB), within the boreal forest region of northwest Ontario, is a region that is expected to be negatively affected by climate warming. Inferences of droughts over the past two millennia from Little Raleigh Lake were based on two nearshore sediment cores. The core locations were from depths of ~12 and 15 m and were based on sufficient nearshore sediment accumulation and distance from the modern benthic-to-planktonic diatom boundary, where a distinct shift from dominance of benthic taxa changed to dominance of planktonic taxa in surficial sediments at ~11.8 m. Diatom-inferred depth was based on a model developed from 60 surficial sediments within the study lake. Depth inferences indicate that prolonged periods of aridity occurred from ~ad 950 to 1300 (corresponds to ‘Medieval Climate Anomaly’) and from ~ad 1625 to 1750 (aridity during ‘Little Ice Age’). We found that the core collected from a depth closer to the benthic-to-planktonic diatom boundary was more sensitive to changes in lake level than the deeper core where planktonic diatoms dominated the assemblage. The inferred low-water stands of the past two millennia are well outside of the range of the past ~100 years, suggesting that recent drought history may not be a good estimate of future extremes.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".