O conhecimento sobre morcegos (Chiroptera: Mammalia) do estado do Espírito Santo, sudeste do Brasil
Bibliographic record
Abstract
(Uploaded by Plazi for the Bat Literature Project) The Order Chiroptera plays a vital role in ecosystem dynamics. Among the states of Southeastern Brazil, Espírito Santo State is the one with the least known bat fauna. This study reports on the current state of knowledge on Espírito Santo bats generating this data bank. We have catalogued the bats deposited in the Biology Museum Prof. Mello Leitão (MBML), Laboratory of Bat Studies of the Federal University of Espírito Santo (LABEQ), Museum of Vertebrate Zoology (MVZ), Royal Ontario Museum (ROM), American Museum of Natural History (AMNH), and University of Michigan Museum of Zoology (UMMZ). In addition, we have investigated the literature seeking articles about bats exclusively for the State. About bats were published in the state 42 papers, three thesis and 11 monographs. There are recognized 63 bat species in the State, if considering the museum collections and published papers, from 37 of the 78 municipalities of Espírito Santo. The highest species richness was found in the municipalities of Linhares and Santa Teresa. This was probably occasioned by bias on sampling. The great potential for new bat occurrences in Espírito Santo is due to the lack of knowledge about bats in this State. This emphasizes the importance for new future studies about bats in that area.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".