A continental‐scale tool for acoustic identification of <scp>E</scp>uropean bats
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Summary Acoustic methods are used increasingly to survey and monitor bat populations. However, the use of acoustic methods at continental scales can be hampered by the lack of standardized and objective methods to identify all species recorded. This makes comparable continent‐wide monitoring difficult, impeding progress towards developing biodiversity indicators, trans‐boundary conservation programmes and monitoring species distribution changes. Here we developed a continental‐scale classifier for acoustic identification of bats, which can be used throughout E urope to ensure objective, consistent and comparable species identifications. We selected 1350 full‐spectrum reference calls from a set of 15 858 calls of 34 E uropean species, from E cho B ank, a global echolocation call library. We assessed 24 call parameters to evaluate how well they distinguish between species and used the 12 most useful to train a hierarchy of ensembles of artificial neural networks to distinguish the echolocation calls of these bat species. Calls are first classified to one of five call‐type groups, with a median accuracy of 97·6%. The median species‐level classification accuracy is 83·7%, providing robust classification for most E uropean species, and an estimate of classification error for each species. These classifiers were packaged into an online tool, i B ats ID , which is freely available, enabling anyone to classify E uropean calls in an objective and consistent way, allowing standardized acoustic identification across the continent. Synthesis and applications . i B ats ID is the first freely available and easily accessible continental‐scale bat call classifier, providing the basis for standardized, continental acoustic bat monitoring in E urope. This method can provide key information to managers and conservation planners on distribution changes and changes in bat species activity through time.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it