Grapevine viruses in Mexico: studies and reports
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
Objective: To contribute to the knowledge of the diversity of viruses and the viral diseases reported in grapevines in Mexico, in order to benefit producers and develop comprehensive viral disease control strategies. Design/methodology/approach: The literature search was conducted in databases such as Scopus, Google Scholar, and EBSCO host, using the following keywords alone or in combination: "virus", "plant", "grapevine", and "Mexico". In addition, the INIFAP database was consulted, alongside undergraduate and postgraduate dissertation theses. Results: Only one academic file was found published in an indexed international journal, using the publication finder software; the report corresponds to a grapevine virus present in Mexico. However, based on all the consulted sources, several viral diseases associated with nine grapevine viruses have been reported in Mexico. These species have been grouped into seven genera and six families. The reports come from Aguascalientes (56%) and Baja California (44%). Three registered viral species are associated with the leafroll complex, three with rugose wood, one with fleck, one with infectious degeneration, and one with red blotch disease. Findings/conclusions: Several grapevine viruses associated with major diseases have been reported in Mexico. Unfortunately, most of the reports lack detail and follow-up, and they are not readily available for international researchers; therefore, the lack of knowledge about this subject in Mexico is significant. Monitoring the epidemiology of viral diseases in the grapevine —a national and international relevant crop— is necessary.
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 | 0.001 | 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 | 0.001 |
| 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