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Update clic/clusters/v1.9.0/README.md

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@@ -74,10 +74,10 @@ The following datasets were used:
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  /eos/user/j/jpata/mlpf/tensorflow_datasets/clic/clic_edm_ww_fullhad_pf/2.2.0
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  ```
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- The truth and target definition was updated in [jpata/particleflow#345](https://github.com/jpata/particleflow/pull/345) have an updated truth and target definition with respect to [Pata, J., Wulff, E., Mokhtar, F. et al. Improved particle-flow event reconstruction with scalable neural networks for current and future particle detectors. Commun Phys 7, 124 (2024)](https://doi.org/10.1038/s42005-024-01599-5).
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- In particular, target particles for MLPF reconstruction are based on status=1 particles.
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- For non-interacting status=1, nearby (dR<0.2) interacting status=0 are used instead.
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  The datasets were generated using Key4HEP with the following scripts:
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  - https://github.com/HEP-KBFI/key4hep-sim/releases/tag/v1.0.0
 
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  /eos/user/j/jpata/mlpf/tensorflow_datasets/clic/clic_edm_ww_fullhad_pf/2.2.0
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  ```
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+ The truth and target definition was updated in [jpata/particleflow#345](https://github.com/jpata/particleflow/pull/345) with respect to [Pata, J., Wulff, E., Mokhtar, F. et al. Improved particle-flow event reconstruction with scalable neural networks for current and future particle detectors. Commun Phys 7, 124 (2024)](https://doi.org/10.1038/s42005-024-01599-5).
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+ In particular, target particles for MLPF reconstruction are based on `status=1` particles.
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+ For non-interacting `status=1`, nearby (dR<0.2) interacting `status=0` are used instead.
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  The datasets were generated using Key4HEP with the following scripts:
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  - https://github.com/HEP-KBFI/key4hep-sim/releases/tag/v1.0.0