A review of the melliferous flora of Yucatan peninsula, Mexico, on the basis for the honey production cycle
Bibliographic record
Abstract
BACKGROUND: The Yucatan Peninsula (YP) is one of the most important regions in global apiculture. Hence, this work reviews and integrates the knowledge of the species diversity, growth habits, ecosystems, floral calendars during the apiculture production cycles and the types of vegetation represented in the melliferous flora (MF) of the YP; as a basis for proposing selection strategies locating suitable apiculture production areas for local beekeepers and help in the economic development of the region. METHODS: A comprehensive review of the MF literature was carried out using the snowball method to determine and update the number of species useful for apiculture. The growth habits and flower calendars were determined through a review of the literature and databases of specimens from the herbaria CICY, UCAM and MEXU. RESULTS: The YP reports a total of 935 taxa of MF (98 families and 498 genera); of these, Campeche has 812 taxa, followed by Quintana Roo (786) and Yucatán (767). The MF is made up of herbs (282), followed by shrubs (260), trees (229), climbers (82), woody climbers (67) palms (14) and parasitic plant (1). CONCLUSION: Of the 935 species of MF registered at the regional level, a high number of species have flowering throughout the year, however, not all of these species are considered useful for local commercial apiculture. Only a select group of 23 species are considered of major importance for local apiculture industry.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".