Contribution to the taxonomic elucidation of the <i>Geonoma maxima</i> complex (Arecaceae) in Central Amazonia, Brazil
Bibliographic record
Abstract
Geonoma maxima (Poit.) Kunth is an example of a species complex, among many others restricted to Neotropical rain forests, which contribute to their high species diversity. Using environmental, morphological, karyological, and molecular data, we aim to test the taxonomic circumscription of 3 of the 11 G. maxima subspecies defined in the latest taxonomic treatment. We evaluated 217 samples of G. maxima complex from Ducke Reserve in the state of Amazonas, Brazil. Environmental preferences were significant at the 0.1% level. Subspecies maxima occurred in the slope, subsp. chelidonura in the floodplain, and subsp. spixiana in the plateau. Leaf morphology and height were different for each subspecies, but not leaf anatomy. The karyotypes of subspp. c helidonura and maxima were symmetrical with 2 n = 28 chromosomes, 16 metacentric and 12 submetacentric. Molecular analysis revealed two groups, one comprised subspp. maxima and chelidonura, and the other formed exclusively by subsp. spixiana. At Ducke Reserve, it is clear that the three subspecies are easily recognizable morphologically and ecologically, and it is likely that they do not interbreed locally. However, if these subspecies are analyzed on a larger geographic scale, it may not be possible to separate them.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".