Adjusting for the effect of missing or dominated plants in progeny and clonal trials of <i>Eucalyptus</i>
Bibliographic record
Abstract
The objective of this paper was to estimate the effect of either missing or dominated plants (those that developed poorly) in experiments evaluating progenies or clones of Eucalyptus. Additionally, it was to investigate whether the use of the area available per plant is a suitable strategy to mitigate the effect of missing plants. Lastly, it was to evaluate whether missing or dominated plants in the experiments affected the association between plant performance in a progeny trial (PT) and their respective clones in a clonal trial (CT). Five 5-year-old PTs and four 3-year-old CTs were used. The recorded trait was diameter at breast height (DBH). The area available per plant was used to carry out the adjustment, taking into consideration the absence of neighboring plants as well as dominated plants. It was found that with the level of missing plants below 20% in experiments, the adjustment using the area available per plant did not improve the efficiency of the selection of either PTs or CTs. The strategy of considering not only missing plants but also dominated plants is not beneficial for the adjustment.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".