Not herbs and forbs alone: pollen‐based evidence for the presence of boreal trees and shrubs in Cis‐Baikal (Eastern Siberia) derived from the Last Glacial Maximum sediment of Lake Ochaul
Bibliographic record
Abstract
ABSTRACT A new accerator mass spectrometry (AMS)‐dated sedimentary record from Lake Ochaul (54°14′N, 106°28′E; 641 m a.s.l.) in Eastern Siberia covers the interval from ca. 27 850 to 20 400 cal a bp at ca. 180‐year resolution and contributes to a better understanding of the complex spatial vegetation pattern during the Last Glacial Maximum (LGM). Non‐arboreal pollen taxa are abundant in the pollen assemblages (mean value ca. 92.6%), but boreal trees are represented by all major taxa that grow in the lake catchment today, including Betula sect. Albae (0.6–4.8%), Picea (0.6–2.8%), Pinus sibirica (Haploxylon type) (up to 1.5%), Pinus sylvestris (Diploxylon type) (up to 2%), Larix (up to 0.6%) and Abies (up to 0.6%). Betula sect. Nanae/Fruticosae (2–5.2%) and Salix (up to 3.2%) are the most representative boreal shrub taxa. Together with existing modern and fossil pollen data from the wider study region, the current record provides further evidence for the long‐debated presence of boreal trees and shrubs in Eastern Siberia throughout the LGM. Our results show that the Upper Lena was a region in which refugia for arboreal taxa existed and that far‐distant pollen transport can be ruled out as the source of the detected arboreal pollen.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".