Multi-proxy paleoenvironmental reconstruction of Deep Lake, Saskatchewan
Bibliographic record
Abstract
A paleoenvironmental reconstruction performed on a lacustrine archive from Deep Lake (DL) located 70 km east of Regina, Saskatchewan, in the Canadian Western Prairie, provides insight into the lake’s past hydrological conditions, water level, nutrients and salinity during mid and late Holocene until modern day. The reconstruction utilizing 14C dating, lithological descriptions, granulometry, diatom analyses , and geochemical XRF analysis, was performed on a 195 cm sediment core (6698 cal yr BP) from the ungauged, shallow (<3 m), and small (3.52 km²) DL reservoir. The results revealed seven distinct zones in the lake's sediment record: 1) From 6698 to 6383 cal yr BP, the lake experienced above average allogenic inputs, low water salinity conditions, and elevated nutrient levels before a 2017 ± 314 year hiatus. 2) Between 4366 and 4067 cal yr BP, there was a decline in allogenic inputs and increase in salinity, indicating arid climate conditions. 3) From 4006 to 3445 cal yr BP, the lake experienced an increase of autogenic deposition, fluctuating water salinity, and fluctuating nutrient levels under arid conditions. 4) From 3391 to 2801 cal yr BP, there was an increase allogenic inputs, decline in salinity, and increase in nutrient levels, indicating wetter climate conditions before a 1018 ± 271 year hiatus. 5) From 1783 to 1068 cal yr BP, there was an increase in autogenic deposition and no diatom deposition or preservation, indicating extremely arid climate conditions. 6) From 923 to 393 cal yr BP, the lake began to transition to modern day conditions with elevated allogenic inputs and elevated salinity. 7) From 256 cal yr BP to present, the lake entered present day conditions with subsaline conditions and elevated nutrient levels. The study of past hydrological and limnological conditions of DL, driven by natural forcings, has provided valuable context for understanding the lake’s modern conditions and its drainage basin.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".