Effects of seedling age on blister rust resistance assessments in eastern white pine and its hybrid backcrosses
Bibliographic record
Abstract
Seedling age at the time of artificial white pine blister rust ( Cronartium ribicola J.C. Fisch.) inoculation can affect the duration and accuracy of resistance assessments for eastern white pine ( Pinus strobus L.) and its hybrid backcrosses and thereby affect advances in breeding programs intended to enhance genetic resistance to the pathogen. Based on postinoculation seedling mortality rates, up to 5 years were required to rank resistance of eastern white pine genotypes when seedlings were inoculated with C. ribicola at 2 years of age compared with less than 2 years when they were inoculated after the first growing season. In this study, we evaluated and compared consistency of genotype rankings in seedling mortality rates between the two inoculation approaches. Assessment results from inoculating seedlings after the first growing season proved as reliable as those achieved by inoculating them after the second growing season. Inoculating seedlings at a younger age not only substantially reduced experimental time and costs but also allowed a larger number of seedlings to be screened for resistance, leading to higher experimental precision.
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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 | 0.001 |
| 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".