apernitch
Automated reproducibility assessment of scientific papers

Drop a paper, get a reproducibility report.

PaperSnitch parses the PDF, classifies the paper, checks it against the MICCAI reproducibility checklist, analyses its dataset documentation and code repository, and returns a 0–100 score with the evidence highlighted in the paper.

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Sample papers
Our-paper-PaperSnitch
The Paper Has a GitHub, the GitHub Has a README, the README Has Nothing: Reproducibility Signals for Review Support
Bolelli Federico, Santoli Davide, Marchesini Kevin, Lumetti Luca, Grana Costantino · MICCAI 2026
Method-paper-with-public-code
A flexible deep learning framework for survival analysis with medical data
Campanella Gabriele, Häggström Ida, Kook Lucas, Hothorn Torsten, Fuchs Thomas J. · MICCAI 2025
New-dataset-and-benchmark
Endplate3D-QCT: A High-Resolution Dataset and Benchmark for Automated 3D Segmentation of Lumbar Vertebral Endplates in QCT
Yin Zixun, Zou Da, Zhao Yi, Zhang Chenbin, Li Weishi, Wu Minghui, Yan Kun, Wang Ping · MICCAI 2025
Large-scale-surgical-dataset
CAT-SG: A Large Dynamic Scene Graph Dataset for Fine-Grained Understanding of Cataract Surgery
Holm Felix, Ünver Gözde, Ghazaei Ghazal, Navab Nassir · MICCAI 2025