Morphological differentiation of Betula (birch) pollen in northwest North America and its palaeoecological application
Bibliographic record
Abstract
Lake sediments from arcto-boreal regions commonly contain abundant Betula pollen. However, palaeoenvironmental interpretations of Betula pollen are often ambiguous because of the lack of reliable morphological features to distinguish among ecologically distinct Betula species in western North America. We measured the grain diameters and pore depths of pollen from three tree-birch species (B. papyrifera, B. kenaica and B. neoalaskana) and two shrub-birch species (B. glandulosa and B. nana), and calculated the ratio of grain diameter to pore depth (D/P ratio). No statistical difference exists in all three parameters between the shrub-birch species or between two of the tree-birch species (B. kenaica and B. papyrifera), and B. neoalaskana is intermediate between the shrub-birch and the other two tree-birch species. However, mean pore depth is significantly larger for the tree species than for the shrub species. In contrast, mean grain diameter cannot distinguish tree and shrub species. Mean D/P ratio separates tree and shrub species less clearly than pore depth, but this ratio can be used for verification. The threshold for distinguishing pollen of tree versus shrub birch lies at 2.55 μm and 8.30 for pore depth and D/P ratio, respectively. We'applied these thresholds to the analysis of Betula pollen in an Alaskan lake-sediment core spanning the past 800 years. Results show that shrub birch increased markedly at the expense of tree birch during the‘Little Ice Age’; this patten is not discernible in the profile of total birch pollen.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".