Evolution of Lecythidaceae with an emphasis on the circumscription of neotropical genera: information from combined <i>ndhF</i> and <i>trnL‐F</i> sequence data
Bibliographic record
Abstract
The Lecythidaceae comprise a pantropical family best known for the edible seeds of the Brazil nut (Bertholletia excelsa) and the cannon-ball tree (Couroupita guianensis), which is planted as a botanical curiosity in subtropical and tropical gardens. In addition, species of the family are often among the most common in neotropical forests, especially in the Amazon Basin. The Brazil nut family is diverse and abundant in the Amazon and is considered to be an indicator of undisturbed or scarcely disturbed lowland forests; thus, what is learned about its evolution, ecology, and biogeography may suggest similar patterns for other Amazonian tree families. We used combined data sets derived from the ndhF and trnL-F genes to elucidate relationships of genera in both the Old and New Worlds that have been associated with Lecythidaceae. Our molecular tree agrees with the recognition of Napoleonaeaceae and Scytopetalaceae. Within the Lecythidaceae, there is molecular support for recognizing three subfamilies: Foetidioideae, Planchonioideae, and Lecythidoideae. We then focused on genera of the Lecythidoideae and found support for recognizing Allantoma (when the actinomorphic-flowered species of Cariniana are included in it), Grias, Gustavia, Corythophora, Couratari, and Couroupita, but conclude that Cariniana, Lecythis, and Eschweilera are not monoyphyletic. Because the position of the monotypic Bertholletia excelsa in relation to the other zygomorphic-flowered genera is not resolved, we are not able to comment on its generic relationships.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".