Relative pollen productivity estimates and changes in Holocene vegetation cover in the deciduous forest of southeastern Quebec, Canada
Bibliographic record
Abstract
The Regional Estimates of VEgetation Abundance from Large Sites (REVEALS) model was used to quantify Holocene changes in vegetation cover in the deciduous forest of southeastern Quebec, Canada. The Extended R-Value (ERV) model was used to obtain relative pollen productivity estimates (PPEs) for eight tree taxa and to determine the relevant source area of pollen (RSAP) for lakes in this ecosystem. Modern vegetation was estimated using pollen data from 16 small (<0.5 km2) lakes and a species-level vegetation survey of southern Quebec. The RSAP was estimated to be within 1600 m of the lakes. Tsuga, Fagus, and Quercus were the most productive taxa, and Populus and Acer were the lowest. Reconstructed changes in absolute vegetation cover show a high abundance of Picea followed by Populus in the early Holocene. The reconstructed values for Populus suggest that it was widely distributed across the landscape. Abies and Acer were dominant on the landscape during the late to mid-Holocene, and an increase in Picea during the Neoglacial is more significant than in percentage diagrams. The REVEALS results provide estimates of land-cover change that are more realistic and informative than the use of pollen percentages alone.
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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 | 0.001 |
| 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 | 0.001 | 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".