Families of loblolly pine that are the most stable for resistance to fusiform rust are the least predictable
Bibliographic record
Abstract
In an extensive series of trials with open-pollinated families of loblolly pine (Pinus taeda L.), resistance to fusiform rust disease (caused by Cronartium quercuum (Berk.) Miyabe ex Shirai f. sp. fusiforme) at individual test sites was relatively unpredictable for the families deemed most resistant. The most resistant families were also the most stable for performance across test sites, with stability defined as the slope of the regression of family means for rust infection versus site means for rust infection. A family's R-50 value (its predicted rust infection level when the site mean infection is 50%) was correlated to its stability parameter or slope (r = 0.78). On average, any one family's level of infection (% galled) was reasonably predictable for any given infection level at a given site; the average coefficient of determination (r2) was 0.78 for the regression of family means for rust infection versus site means for rust infection. However, the six most stable families for resistance had the lowest r2 values (average r2 = 0.58). We speculated that the lower predictability for the most resistant families was due to interactions of specific resistance genes in these families and corresponding avirulence and (or) virulence levels in the pathogen populations that may differ among sites. Although the predictability of the individual resistant families was relatively low, if these families were bulked into a resistant seed lot, they performed in a more predictable manner with r2 = 0.74 for the regression of the bulk mean versus site means. Bulks of four to six highly resistant families appeared to be a good solution to obtain stable and predictable performance across a range of sites.
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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) | 0.001 | 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 | 0.001 |
| 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".