arXiv v2: benchmark link, ORCID byline, card corrections

README.md

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 # Model Card for DALE-CT-0
 
-**Authors:** [Evan W. Damron](https://huggingface.co/evn13) · Mahmut S. Gokmen · Mitchell A. Klusty · Caroline N. Leach · Emily B. Collier · V. K. Cody Bumgardner — Institute for Biomedical Informatics Center for Applied AI (IBI-CAAI), University of Kentucky
+**Authors:** [Evan W. Damron](https://huggingface.co/evn13) ([ORCID 0009-0009-1104-3202](https://orcid.org/0009-0009-1104-3202)) · Mahmut S. Gokmen · Mitchell A. Klusty · Caroline N. Leach · Emily B. Collier · V. K. Cody Bumgardner — Institute for Biomedical Informatics Center for Applied AI (IBI-CAAI), University of Kentucky
 
 This repository hosts the backbone weights for DALE-CT-0 (Depth-Aware Latent-Euclidean Computed Tomography), a foundational Vision Transformer (ViT-Large) trained on Chest CT scans using the Latent-Euclidean Joint-Embedding Predictive Architecture ([LeJEPA](https://github.com/galilai-group/lejepa)) framework. 
 
@@ -48,9 +48,9 @@ See the paper for the full protocol and confidence intervals.
 | [DALE-CT-2S](https://huggingface.co/Kentucky-Open-Science/DALE-CT-2S) | **0.8247** | 0.6252 / 0.7389 | Best in-domain (CT-RATE) |
 | [DALE-CT-1S-v2](https://huggingface.co/Kentucky-Open-Science/DALE-CT-1S-v2) | 0.8098 | 0.6284 / 0.7334 | Anatomical (TotalSegmentator) dense supervision only |
 | [DALE-CT-0](https://huggingface.co/Kentucky-Open-Science/DALE-CT-0) | 0.8057 | 0.5946 / 0.7477 | Pure self-supervised, CT-RATE |
-| [Finetuned DINOv2](https://huggingface.co/Kentucky-Open-Science/Finetuned-DINOv2-Chest-CT) | 0.7953 | 0.6252 / 0.7550 | Continual-pretraining baseline |
+| [Finetuned DINOv2](https://huggingface.co/Kentucky-Open-Science/Finetuned-DINOv2-Chest-CT) | 0.7953 | 0.6252 / 0.7550 | Continual-pretraining baseline — strongest dense (patch-level) features |
 
-**Paper:** [DALE-CT: Depth-Aware 2D Slice Encoders Learn an Anatomical World Model of Chest CT](https://arxiv.org/abs/2606.07775) · **Code:** [Kentucky-Open-Science/DALE-CT](https://github.com/Kentucky-Open-Science/DALE-CT)
+**Paper:** [DALE-CT: Depth-Aware 2D Slice Encoders Learn an Anatomical World Model of Chest CT](https://arxiv.org/abs/2606.07775) · **Code:** [Kentucky-Open-Science/DALE-CT](https://github.com/Kentucky-Open-Science/DALE-CT) · **Benchmark:** [Kentucky-Open-Science/chest-ct-foundation-model-benchmark](https://github.com/Kentucky-Open-Science/chest-ct-foundation-model-benchmark)
 
 ## Model Details
 * **Model Type:** Vision Transformer (ViT-Large) for Chest CT analysis.