The potential for palaeoclimate records from varved Arctic lake sediments: Baflin Island, Eastern Canadian Arctic
Bibliographic record
Abstract
Abstract: Tidewater lakes on Baflin Island in the eastern Canadian Arctic offer an excellent opportunity to study interannual to century-scale Arctic climatic change. Freeze-cores were analysed from three lakes in southeastern Baffln Island: Upper Soper Lake, Ogac Lake and Winton Bay Lake. The sediment record in each lake consists of massive sediments overlain by an organic-rich, finely laminated section which continues to the surface. The laminae in Ogac Lake were studied in detail and consist of two types. The light layers are composed almost entirely of intact diatom frustules, primarily Chaetoceros spp. The darker layers are dominated by clay and silt-sized terrigenous mineral grains, including abundant quartz and feldspars. These couplets are probably deposited as the result of diatom blooms in the late spring/summer growing season followed by settling of grains introduced by summer runoff. Sedimentation rates based on 21 ~ dates agree well with rates based on laminae counts in both Ogac and Winton Bay Lakes, indicating that the laminae couplets are annually deposited varves. Our experience suggests that shallow-silled tidewater lakes with varved sediments may be relatively common along the coast of Batiin Island. It should thus be possible to create a network of sites with annually dated palaeoclimate r cords.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".