Trends in growing space efficiency of four boreal forest species based on yield table data
Bibliographic record
Abstract
Yield tables are used to identify trends in growing space efficiency (GSE) and to relate GSE to self-tolerance and intraspecific competition. The method is useful when data specifically collected for this purpose are not available. Plonski’s normal yield tables for jack pine (Pinus banksiana Lamb.), paper birch (Betula papyrifera Marshall), trembling aspen (Populus tremuloides Michx.), and black spruce (Picea mariana (Mill.) B.S.P.) are used. An exponential volume–age function was partitioned into volume–area and area–age functions. The exponents of these two components form the B/D ratio, which is used to determine the mode of the stand at a given time, e.g., if B/D is <3/2, then the stand is in area occupation mode, and if B/D is >3/2, then the stand is in area exploitation mode. The dominant mode is the one most responsive to availability of growth resources, showing greater acceleration when resources are plentiful and more rapid deceleration when resources are scarce. Jack pine and paper birch are identified as area occupiers, whereas trembling aspen and black spruce are area exploiters and are therfore self-tolerant. Asymmetric competition was deemed to be present for paper birch throughout the life of the stand on site class I and for trembling aspen on all sites prior to senescence.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| 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".