Diaspore

Explore: search the science and map a field

Put in a topic and a date. Get the labs working on it and what their papers claim, using only what was published by that date. Then test your own picks against what happened, and read what the full evaluation produces.

Map a field: who had public evidence on a topic, as of a date

Labs, institutions and companies with public evidence on a target or topic by your date, and how the field filled up year by year. Other public names for the same target are searched too. Or start from the list of targets.

Pick your own, then see what happened

It is 2022-12-31. Each set shows 10 young health companies with their names hidden and everything public about them that day. Pick the ones you think raise a seed round or larger within 24 months. Then the page shows what happened, with the model's picks and the blind AI's picks beside yours.

The sets are easier than real life and the page says so: 3 of every 10 came true here, against 7% of 1,097 companies in the full test. Over many sets drawn the same way, the model's top picks find 1.5 on average, the blind AI's 1.6, and random picks 0.9. There are 12 sets, all from one test: new company to seed round. Other stages have no deck yet. The model and the blind AI also saw one line you do not: whether an officer's name matched a lab head. A name match is not shown anywhere on this site, so it is left off the cards.

Evidence briefs, built ahead of time

A brief is what the full evaluation produces for a topic or a lab: the search above finds the papers, a sealed reader checks each extracted claim against the abstracts and must return two exact quotes, and code checks the quotes and sorts. It needs reader agents, so this page cannot run it. These 6 were built by the real pipeline on the dates shown.

Across them: 100 of 103 claims were verified against their own paper. The reader found 0 contradictions and 0 cases where a second, independent lab supports a claim. A brief is a checked, quoted listing of the evidence.