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