Variation among provenances and families of blackbutt (<i>Eucalyptus pilularis</i>) in early growth and susceptibility to damage from leaf spot fungi
Bibliographic record
Abstract
Growth to 38 months and severity of Mycosphaerella leaf disease and target spot (caused by Aulographina eucalypti (Cooke & Mass.) von Arx & Muller) were assessed in a Eucalyptus pilularis Smith (blackbutt) family trial in New South Wales (NSW), Australia. Significant variation in growth, disease, and defoliation was found among the 40 provenances and 321 families tested; however, relatively few provenances had concentrations of superior or poor families. Most families in three higher altitude NSW provenances were superior for volume increment, while three southeast Queensland provenances had low mean volume increment. Mycosphaerella damage and defoliation tended to be low in several higher altitude northern NSW provenances, but the southeast Queensland provenances had significantly higher mean defoliation. Individual narrow sense heritability estimates were low to moderate for Mycosphaerella damage (0.38) and defoliation (0.22) and low for Aulographina damage (0.13) and volume increment (0.13). Significant genetic and phenotypic correlations between Mycosphaerella damage and defoliation were low and positive. Low to moderate negative correlations occurred between Mycosphaerella damage and volume increment and between defoliation and volume increment, suggesting that Mycosphaerella leaf disease, in particular, and defoliation had deleterious effects on tree growth. However, the impact of these foliar pathogens on the volume of E. pilularis is often low, so selecting for growth and form alone in the early stages of domestication could provide acceptable gains in yield.
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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 | 0.001 | 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".