A ready-to-use version of the Eurasian modern pollen database 2 (EMPD 2; Davis et al., 2020) for paleoclimatic reconstructions
Bibliographic record
Abstract
Pollen-based paleoclimatic reconstructions based on calibration or analogue techniques require large collections of modern pollen samples, which together contain a very high number of pollen taxa. For paleoclimate reconstructions, however, the number of taxa needs to be reduced so the taxonomical resolution of modern and fossil pollen samples can be compatible. Version 2 of the Eurasian modern pollen database (EMPD2) (Davis et al., 2020) is the largest compilation of modern pollen samples covering these regions and comprises 840 pollen taxa. However, it cannot be used easily without homogenizing the taxonomic entities by grouping at genus or family levels or discarding certain rare taxa. This task is essential but time-consuming. Here, we present a ready-to-use homogenized version of the EMPD2 that comprises 90 pollen taxa, and which is adapted for paleoclimatic reconstructions in the Eurasian region.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.040 | 0.030 |
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".