Automated, immutable and auditable.
No human touches the scan, ranking, or publication steps. An automated weekly process runs the full pipeline and exports results directly to a public GitHub repository. The website reads from there — every data point carries an immutable commit timestamp, independently verifiable by anyone.
How integrity is enforced
Scheduled, unattended
The scan, ML ranking, and data export run on a fixed weekly automated schedule with no human input between runs. The pipeline cannot be selectively triggered, paused mid-cycle, or re-run with different inputs.
No partials
Each week's output is either fully published or not published at all. If the pipeline fails partway through, the previous week's data stays intact — there is no in-between state.
Locked, then revealed
Candidates are encrypted and committed the moment a scan completes — proof of timing without revealing them to free users yet. The key is published alongside the plaintext 12 weeks later, so anyone can verify nothing changed in between.
Outcome lockout
Outcome files are written exactly once at 12 weeks. The system has no modification path after initial write. What the model ranked at scan time is permanently what the archive shows.
Verify it yourself
The public data repository contains every exported file with its full commit history. Inspect when any scan was published, compare any two exports, and confirm no file was modified after its initial commit.