Post-glacial diatom-inferred aquatic changes in Sicamous Creek Lake, British Columbia, Canada
Bibliographic record
Abstract
Diatom analyses of sediments from a high elevation lake situated in an Engelmann Spruce - Subalpine Fir (ESSF) forest of south-central British Columbia, Canada, reveal long-term climate and water chemistry change. During the transition from the late-glacial / Pleistocene to the xerothermic early Holocene, small, benthic Fragilaria diatoms species that grew under low light conditions in Sicamous Creek Lake gave way to planktonic Cyclotella species that require open-water conditions. Warm temperatures in the mesothermic Holocene are indicated by smaller Cyclotella species and large, benthic pennate diatoms. Diatom communities reflected Neoglacial cooling in the late Holocene, with abundant Nitzschia fonticola and Achnanthes minutissima. Small, benthic Fragilaria regained abundance, suggesting cooling and conditions similar to the late-glacial interval. Diatom community composition responded to the deposition of the Mt. Mazama and Mt. St. Helens tephras, though the Mazama eruption caused greater change in relative abundance of various taxa within the assemblage. Correspondence analysis shows distinct communities have occurred since the initiation of sedimentation, likely due to climate controlled landscape and vegetation changes; diatom-inferred pH values using various models and training sets show limited acidification change occurred through the lake’s history.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".