DENDROCLIMATOLOGY OF EASTERN WHITE CEDAR (THUJA OCCIDENTALIS L.) AT LAKE HÉBÉCOURT, QUÉBEC
Bibliographic record
Abstract
The objective of this study was to evaluate the dendroclimatic potential of eastern white cedar at Lake Hébécourt in northwestern Québec. We did this by conducting response function analyses with ring-width chronologies developed from trees representing different growth conditions. Material and methods On five islands in Lake Hébécourt, a total of 41 white cedar trees were sampled, which represented the following three growth conditions: i) 12 shoreline trees that are inundated at least during periods of high water levels (shore), ii) 16 relatively small and twisted trees rooted within cracks in cliff faces and growing about 2 m above the maximum water level (cliffs), and iii) 13 trees located in the interior of the forest more than 2 m above the lake and growing on relatively deep soil (forest interior). Using an increment borer, one to three cores were taken from each tree, glued on wooden supports, and then sanded. The samples were crossdated using pointer years, that is years where ring widths were much larger or smaller than the average. Tree-ring widths were measured and crossdating was verified statistically with the program COFECHA. The measurement series were detrended by negative exponential functions and chronologies were developed separately for each of the three sites with the program ARSTAN. The relationship between the residual chronologies (i.e., ring-width indices) and climate was analyzed for
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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 | 0.001 |
| 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) | 0.001 | 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 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".