In Silico Characterization of the Phytopathogenic Efector, avr3a, from Phytophthora cinnamomi
Bibliographic record
Abstract
Phytophthora cinnamomi is an Oomycete considered one of the most widespread and destructive pathogens on the planet. Its geographic presence is cosmopolitan and the range of hosts is regarded as one of the largest. This pathogen causes enormous economic damages to important cultures worldwide; this has helped to attract the attention of the scientific community. It is the causal agent of chestnut ""ink"" disease (Castanea sativa Miller).The chestnut tree has different applications, besides chestnut and wood, it plays an important role in soil ecology and biodiversity. Therefore it is important to know the molecular mechanisms (genes and proteins) that are the basis of the Castanea sativa infestation process by Phytophthora cinnamomi and the nature of the pathogen-host interaction in order to establish strategies to combat and control this parasite.With bioinformatics tools, we were able to identify and characterize the Avr3a gene in genomic sequences of P. cinnamomi deposited in the Databases. This gene encodes a recognized 209 aminoacids, protein in the host cytoplasm where it triggers cell death.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".