Height growth of planted black spruce seedlings in response to interspecific vegetation competition: a comparison of four competition measures at two measuring positions
Bibliographic record
Abstract
Four simple measures of interspecific competition (percent cover visually estimated in the field, percent cover derived from hemispherical photographs, percent full sunlight measured by a ceptometer, and gap light index derived from hemispherical photographs) obtained at two reference positions (the top and the middle of crop seedlings) were evaluated in relation to two growth variables (relative height growth rates in 1998 and during 1996 to 1998) of black spruce (Picea mariana (Mill.) BSP) seedlings planted on boreal mixedwood sites in southeastern Manitoba. The four competition measures assessed at the two measuring positions explained 57.2-68.0% of the total variation in black spruce height growth rate. Significant relationships were found among the four measures, and between the two measuring positions for each measure. The measuring position was not critical for all competition measures except the percent full sunlight measured by the ceptometer, for which the middle position was much better. When assessed at their preferred positions, the four competition measures ranked as follows: (i) percent cover derived from hemispherical photographs or percent full sunlight measured by the ceptometer; (ii) gap light index derived from hemispherical photographs; and (iii) visually estimated percent cover of vegetation.
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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 | 0.000 | 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) | 0.000 | 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".