The underestimated diversity of phytoplasmas in Latin America
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
Phytoplasmas ('Candidatus Phytoplasma') are insect-transmitted, cell-wall-less, plant-pathogenic bacteria that cause economically important crop diseases. Because phytoplasmas are difficult or impossible to culture in vitro, they are classified taxonomically according to the convention used for unculturable micro-organisms. The first coherent scheme of classification of phytoplasmas, based on the RFLP pattern of the 16S rRNA-encoding gene generated with 17 restriction endonucleases, was updated several times until the development of the iPhyClassifier. iPhyClassifier is an interactive online tool capable of determining the species, group and subgroup of 'Candidatus Phytoplasma' of unknown samples using the 16S F2nR2 sequence. Latin America, an important geographical area in relation to food production, has a high incidence of plant diseases caused by phytoplasmas. However, many phytoplasmas associated with these diseases have not been properly classified. An extensive literature review and the use of iPhyClassifier allowed us to identify two new tentative groups (16SrXXXIII-A and 16SrXXXIV-A) and the following tentative new subgroups among Latin American strains that were either previously unclassified or misclassified: six in 16SrI, six in 16SrII, one in 16SrIII, one in 16SrVII, one in 16SrIX, one in 16SrXII and two in 16SrXIII.
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