Pollen‐based biomes for Beringia 18,000, 6000 and 0 <sup>14</sup>C yr <scp>bp</scp><sup>†</sup>
Bibliographic record
Abstract
Abstract The objective biomization method developed by Prentice et al . (1996) for Europe was extended using modern pollen samples from Beringia and then applied to fossil pollen data to reconstruct palaeovegetation patterns at 6000 and 18,000 14 C yr bp . The predicted modern distribution of tundra, taiga and cool conifer forests in Alaska and north‐western Canada generally corresponds well to actual vegetation patterns, although sites in regions characterized today by a mosaic of forest and tundra vegetation tend to be preferentially assigned to tundra. Siberian larch forests are delimited less well, probably due to the extreme under‐representation of Larix in pollen spectra. The biome distribution across Beringia at 6000 14 C yr bp was broadly similar to today, with little change in the northern forest limit, except for a possible northward advance in the Mackenzie delta region. The western forest limit in Alaska was probably east of its modern position. At 18,000 14 C yr bp the whole of Beringia was covered by tundra. However, the importance of the various plant functional types varied from site to site, supporting the idea that the vegetation cover was a mosaic of different tundra types.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".