A phylogenetic framework to study desirable traits in the wild relatives of <i>Theobroma cacao</i> (Malvaceae)
Bibliographic record
Abstract
Abstract Crop wild relatives (CWRs) of cultivated species may provide a source of genetic variation that can contribute to improving product quantity and quality. To adequately use these potential resources, it is useful to understand how CWRs are related to the cultivated species and to each other to determine how key crop traits have evolved and discover potentially usable genetic information. The chocolate industry is expanding and yet is under threat from a variety of causes, including pathogens and climate change. Theobroma cacao L. (Malvaceae), the source of chocolate, is a representative of the tribe Theobromateae that consists of four genera and c. 40 species that began to diversify over 25 million years ago. The great diversity within the tribe suggests that its representatives could exhibit advantageous agronomic traits. In this study, we present the most taxonomically comprehensive phylogeny of Theobromateae to date. DNA sequence data from WRKY genes were assembled into a matrix that included 56 morphological characters and analyzed using a Bayesian approach. The inclusion of a morphological data set increased resolution and support for some branches of the phylogenetic tree. The evolutionary trajectory of selected morphological characters was reconstructed onto the phylogeny. This phylogeny provides a framework for the study of morphological and physiological trait evolution, which can facilitate the search for agronomically relevant traits.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".