Panoscope

Panoscope is a grounded interpretation layer over jazzPanda's spatial-transcriptomics output. A wet-lab biologist opens a cluster and asks in plain language, for example "why is this still Stromal when COL1A1 is missing?", and Panoscope answers with a cell-type call, a confidence band, the driving markers with their real jazzPanda numbers, and a live-fetched PubMed citation for the biology. It never invents a marker, a number, or a reference. Two design choices make it trustworthy. A confident floor: a deterministic engine computes every confidence band from jazzPanda's spatial signal and enforces the panel-absence rule, so a canonical marker that was never on the 280-gene panel is not treated as evidence against a cell type. An open ceiling: literature reasoning runs live through Claude behind a grounding gate that rejects any number or citation it cannot trace to source, and a test suite fails the build if the agent states anything it cannot cite. When a biologist overrides a call, Panoscope keeps their decision and cross-checks the literature, saving a versioned, git-tracked lab note with both the agreement and the dissent visible. The same discipline extends past marker calls. A second workflow interprets gene-set enrichment on the panel, carrying a mandatory panel-coverage caveat (for example, only 8 of a 200-gene program are actually measured) that deterministically weakens the confidence when a "pathway" really rests on a handful of immune genes bleeding in from neighbouring cells. Each analysis method is a self-contained skill file, so supporting a new bioinformatics tool means writing a new grounded interpretation contract, not a new app. Why it matters: annotation confidence is exactly where biologists get stuck, and LLMs are exactly where fabrication creeps in. Panoscope is a reusable pattern for Claude Science: put Claude on top of any real bioinformatics output and make it structurally unable to state a fact it cannot cite. Every one of the 223 citations it ships resolves to a real paper.