Growth and productivity of black spruce (
Bibliographic record
Abstract
\n • The managed area of the North-American boreal forest has been studied extensively.\n However, because of their inaccessibility, the growth and dynamics of trees at higher\n latitudes remain unknown, so precluding the possibility of quantifying their productive\n and economic potential and, if any, their exploitation. \n • The aim of this paper was to assess individual growth patterns in dominant black\n spruces (Picea mariana (Mill.) B.S.P.) belonging to the first cohort and\n to compare growth dynamics within and north of the commercial forest in Quebec, Canada. \n • Compared with stands located on 49th parallel, stands on 51st parallel showed thinner\n tree rings and 15% less growth in height, resulting in a 35% reduction in the stem volume\n attained at the age of 125 years (170 and 110 dm3 for dominant trees in stands\n within and north of the commercial forest, respectively). At maturity, the annual\n increment in stem volume in northern stands was 28% lower than that measured in southern\n stands. \n • These findings represent important information on tree growth in stands of\n high-latitude boreal forests and should be taken into account when evaluating the\n profitability of exploiting the remotest Canadian forests. Confirmation by more extensive\n and spatially-exhaustive inventories is desirable.\n
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".