A comparison of pre-European settlement (1857) and current (1981-1995) forest composition in central Ontario
Bibliographic record
Abstract
Presettlement forest composition along a 278 km long transect through central Ontario was recreated from Ontario land survey notes (1857) and compared with existing forest composition as derived from Forest Resource Inventories (1981-1995). Trends through time were analyzed by means of detrended correspondence analysis and univariate statistics (paired t tests and Wilcoxon matched-pair signed-ranks tests). Ordinations based on the first tree taxon listed in a stand and on all tree taxa provided similar results. The eastern half of the transect was initially dominated by boreal conifers, whereas the western half supported stands typical of Ontario's Great Lakes - St. Lawrence (GLSL) region. Significant reductions of yellow birch (Betula alleghaniensis Britt.), balsam fir (Abies balsamea (L.) Mill.), and eastern white cedar (Thuja occidentalis L.) and significant increases of poplar (Populus spp.) and white birch (Betula papyrifera Marsh.) were observed within the boreal half. A significant reduction in eastern white cedar and an increase poplar were observed in the western half. Changes in the boreal region strongly support previous studies conducted over shorter time periods and may be attributed to clear-cut harvesting. The persistence of shade-tolerant hardwoods within the GLSL region can be attributed to the prevalence of small-scale disturbances associated with partial-cut harvesting systems.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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".