Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Effective breeding for disease resistance relies on a thorough understanding of host-by-pathogen relations. Achieving such understanding can be difficult and challenging, particularly for large data sets with complex host genotype-by-pathogen strain interactions. This paper presents a biplot approach that facilitates visual analysis of host-by-pathogen data. A biplot displays both host genotypes and pathogen isolates in a single scatter plot; each genotype or isolate is displayed as a point defined by its scores on the first two principal components derived from subjecting genotype- or strain-centered data to singular value decomposition. From a biplot, clusters of host genotypes and clusters of pathogen strains can be simultaneously visualized. Moreover, the basis for genotype and strain classifications, i.e., interactions between individual genotypes and strains, can be visualized at the same time. A biplot based on genotype-centered data and that based on strain-centered data are appropriate for visual evaluation of susceptibility/resistance of genotypes and virulence/avirulence of strains, respectively. Biplot analysis of genotype-by-strain is illustrated with published response scores of 13 barley line groups to 8 net blotch isolate groups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 it