Eugenia tikalana Lundell, Wrightia
Bibliographic record
Abstract
72. Eugenia tikalana Lundell, Wrightia 2: 210 (1961a) EOO: 155,110.419 km ². AOO: 276 km ². Evaluation of IUCN: Least Concern. Eugenia tikalana occurs from southeastern Mexico to Guatemala and Belize (Barrie 2020, WCSP 2020). One hundred and eighteen collection records are known, including the Yucatan Peninsula, which covers the southeast of Mexico with the states of Campeche, Yucatán and Quintana Roo, but it also has influence in Belize and a part of the territory that belongs to Guatemala. The estimated extent of occurrence (EOO) exceeds the thresholds for a threatened category under the criterion B, as well as the area of occupancy (AOO) would probably exceed the thresholds for any threatened category if the remaining habitat available is taken in account. The occurrence biome is the Humid Tropical Forest, the species being an element of primary and secondary forests, from 13 to 950 m elev. Important collections have been recorded in biodiversity conservation areas in Mexico, Guatemala, and Belize, such as Calakmul Biosphere Reserve, the Maya Biosphere Reserve, the Sierra Lacandon National Park, and the Mountain Pine Ridge Forest Reserve. Therefore, Eugenia tikalana is classified here as Least Concern (LC) (BGCI & IUCN 2019i). Specimens examined:— MEXICO. Campeche: Zamora & Hernández 4458 (MEXU!); Chiapas: Durán & Levy 90 (MEXU!); Quintana Roo: Duran 2758 (K!); Yucatán: Darwin et al. 2177 (MEXU!). Belize: Gentle 1026 (MO); Guatemala: Contreras 7626 (LL).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.054 | 0.014 |
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".