Height–Diameter Relationships for Jack Pine Seedlots of Different Genetic Improvement Levels
Bibliographic record
Abstract
Abstract Differences in height-diameter (H-DBH) relationship were investigated using the Chapman-Richards function among jack pine seedlots planted in a realized genetic gain test in New Brunswick. Three seedlots representing the bulk mixed cone collection from the 1979 J.D. Irving’s first-generation seedling seed orchard (JDISSO) before rogueing (UNR), after the first time genetic rogueing (1STR) and after the second time genetic rogueing (2NDR), respectively, were planted in the test. Unimproved commercial seedlots (UC) were also included for comparison. Results indicate that an overall H-DBH relationship for all the seedlots was not appropriate. Seedlot pairwise comparisons in H-DBH relationships showed that, whereas most seedlot pairs were significantly different from each other, there was no significant difference between the UNR and UC and between the 1STR and 2NDR. Two models were developed with one targeting the UNR and UC (UNIMPROVED) and the other targeting the 1STR and 2NDR (IMPROVED). The difference between the UNIMPROVED and IMPROVED models was caused only by asymptote of the Chapman-Richards function. Applying the UNIMPROVED or IMPROVED model to predict height of the 1STR and 2NDR or the UNR and UC would result in an under-estimated or an over-estimated bias by 2 to 3% in height. In light of this study, seedlot differences in H-DBH relationships should be integrated into growth and yield models by a multiplier for height depending on genetic improvement levels.
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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 | 0.000 | 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".