Molecular Detection and Quantification of<i>Pythium</i>Species: Evolving Taxonomy, New Tools, and Challenges
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
The genus Pythium is one of the most important groups of soilborne plant pathogens, present in almost every agricultural soil and attacking the roots of thousands of hosts, reducing crop yield and quality. Most species are generalists, necrotrophic pathogens that infect young juvenile tissue. In fact, Cook and Veseth have called Pythium the "common cold" of wheat, because of its chronic nature and ubiquitous distribution. Where Pythium spp. are the cause of seedling damping-off or emergence reduction, the causal agent can easily be identified based on symptoms and culturing. In more mature plants, however, infection by Pythium spp. is more difficult to diagnose, because of the nonspecific symptoms that could have abiotic causes such as nutrient deficiencies or be due to other root rotting pathogens. Molecular methods that can accurately identify and quantify this important group are needed for disease diagnosis and management recommendations and to better understand the epidemiology and ecology of this important group. The purpose of this article is to outline the current state-of-the-art in the detection and quantification of this important genus. In addition, we will introduce the reader to new changes in the taxonomy of this group.
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) | 0.000 | 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