Methods²

The platform

CiteZero captures experiments where they happen, at the bench, as part of work the lab already does. We never ask anyone to write up a failure: every condition is logged as it is tried, before anyone knows what will work. What the lab doesn't carry forward becomes the record that is missing today.

What researchers get

A tool is only used if it saves more time than it costs. CiteZero is built to take work away from the researcher, not add to it.

• Plan

  Start from your lab's own protocols, filled in automatically. A controls checklist that says what is missing and what each control proves, a sample-size calculator, and printable bench sheets.

• Publish

  A publication-ready methods paragraph and an ELN table, generated from what you recorded — with RRIDs and lot numbers already in place.

• Learn

  A searchable record of everything your lab has tried, including what failed and why — so nobody repeats last year's dead end. Once the shared pool opens, what other labs found too, de-identified.

• Start without the typing

  Import existing inventories, protocols and your lab's own papers. AI extraction turns them into structured records, and you review everything before it is saved. It is optional, and only runs with your consent.

Science is not one size fits all

A western blot, a qPCR run and a CRISPR screen have almost nothing in common: different protocols, different inventories, different ways to fail. A single generic form would capture none of them well. So CiteZero is a family of apps — one for each type of experiment, each built around its own protocols, reagents and inputs — all feeding one shared record.

Later, a study layer will tie them together: one question, one hypothesis, and the experiments across methods that tested it — including the ones that disagreed.

First app: antibodies

Antibodies are used in almost every wet lab, across fields. We rely on the same reagents and similar protocols, and keep testing and failing the same conditions without learning from each other. That makes a huge pile of data that is easy to recycle — so that is where we start.

Your data stays yours

• Institutions own their labs' records. We never share, sell or license them — only statistics derived from them.

• Sharing is opt-in, per lab, and needs an agreement with the lab's institution.

• De-identified and aggregated. A statistic is used only when enough labs, from several institutions, report the same condition — and only after a delay.

• Any experiment can be held back from the pool, whatever the lab's sharing choice.

What's next

Antibodies are the start. The same logic extends to the other experiments every lab runs:

• Primers & qPCR

  Run daily in every molecular lab. No amplification, dimers, off-targets — failures nobody currently shares.

• siRNA & shRNA

  Which knockdown reagents actually silenced the target, and which quietly didn't.

• CRISPR guides

  Guide efficiency varies from lab to lab. Pooling the low-efficiency guides nobody publishes turns dead ends into prediction.