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What BatDetect2 predicts
BatDetect2 predicts call-level events, not recording-level truth.
For each retained detection, the current stack can expose:
- a geometry describing where the event sits in time-frequency space,
- a detection score,
- a class-score vector,
- an internal feature vector.
Detection score versus class scores
These are different outputs and should not be interpreted as the same thing.
- The detection score is about whether the event is kept as a detection.
- The class-score vector ranks classes for that detected event.
A detection can be kept while still having uncertain class identity.
Predictions are conditional on the workflow
The final output also depends on:
- preprocessing,
- postprocessing,
- thresholds,
- target definitions,
- output transforms.
That is why two runs can differ even when they use the same checkpoint.
What BatDetect2 does not predict
BatDetect2 does not directly output ecological truth.
It also does not eliminate the need for local validation.
Use reviewed local data before making ecological claims.
Related pages
- Model output and validation: {doc}
model-output-and-validation - Postprocessing and thresholds: {doc}
postprocessing-and-thresholds - Interpreting formatted outputs: {doc}
interpreting-formatted-outputs