Distribution of the bat Family Mormoopidae in Honduras
Bibliographic record
Abstract
Honduras is the second country in central America along with Panamá with the greatest bat diversity, and the insectivorous bats are the most diverse in the Chiroptera order. The family Mormoopidae has the largest number of records in Honduras and these bats are important as pest control in crops where they are present. To understand the importance of the Mormoopidae family in Honduras, we need to know where it is distributed. A species distribution model is a tool that provides information on the distribution of the species, based on presences records and climate variables. We collected information from free access databases like GBIF, reports, and paper publication to obtain presence data in Honduras. To run the models, we used Maxent in dismo package. Our results show a similar distribution for all species of Mormoopidae family, the principal causes that limited the distribution of the species are ecosystem type and altitude; some species tolerated evergreen forest and others prefer dry forest, in terms of elevation, in some species is limited from lowland to 1500 m.a.s.l., like Mormoops megalophylla, Pteronotus psilotis, and Pteronotus gymnonotus, and others can inhabit above 2800 m.a.s.l., like Pteronotus fulvus, and Pteronotus mesoamericanus. We need to obtain more records of species like M. megalophylla, P. psilotis, and P. gymnonotus. More surveys in the eastern part of Honduras are necessary where there are many information gaps, this would help us to have more robust models and a better understanding of the distribution of these species.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".