{"paper":{"title":"Adaptive spatial blocking for scalable clustering inference with applications to high-throughput spatial proteomics","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Hoseung Song, Julia Wrobel, Mingyu Go","submitted_at":"2026-06-10T12:45:50Z","abstract_excerpt":"Ripley's K-function is a widely used spatial summary statistic for assessing clustering in point patterns. However, existing K-based methods can be computationally prohibitive for large-scale data, particularly in high-throughput spatial proteomics, because they rely on spatial information from all points in the image. To address this challenge, we propose a computationally efficient block-based testing framework that extracts disjoint local blocks from an image and aggregates clustering evidence across them. The proposed adaptive spatial blocking algorithm constructs blocks satisfying point-c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.12021","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2606.12021/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}