Spatial patterns of pollen deposition in arctic snow
Bibliographic record
Abstract
The pollen content of 77 snow samples, collected at 41 sites in the Canadian Arctic, the adjacent Arctic Ocean and Greenland can be used to identify source regions that produced the assemblages. The major vegetation zones of northern Canada produce distinctive pollen assemblages, and principal components analysis (PCA) indicate that these assemblages are retained even in snow on the sea ice surface. It is shown that pollen percentages and concentrations are related to the density of the regional vegetation and to the distance to the source of more productive regions. Because the pollen grains may be transported for great distances (even to the central regions of the Arctic Ocean), they may be used to indicate the source of that pollen and the trajectory of the air masses that carried and deposited them. Pine is particularly valuable in this sense because it has longer trajectories than other tree pollen. For example, there are indications of “over‐the‐pole” transport of pollen from higher pine pollen concentrations at the North Pole than on northern Ellesmere Island. Pollen concentrations of certain taxa change significantly at ∼75°N, north of which the concentrations become lower, thereby suggesting that there is a climatic boundary at that latitude. Therefore it would appear that studies of the concentration of pollen in snow have the potential for determining past and present characteristics of atmospheric circulation and also for helping in the development and interpretation of paleoenvironmental records in regions without vegetation, such as ice caps.
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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 | 0.001 | 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".