analyze_media_age.py claimed age was ruled out because an image from
2025-11 was saved while one from 2026-08 was not. That conclusion does not
follow. "Saved" means some earlier run downloaded it, not that ChatGPT
still holds it — an image captured in June looks saved forever after, even
if it died in July. A month with no losses shows the exports were timely,
not that the assets survived.
- probe_survival_by_month.py: sample images already on disk, grouped by
their conversation's month, and ask /files/{id} whether each still
exists today. Old months still 200 → no expiry, and cadence did not save
them. Old months now 404 → uploads do expire and cadence is the whole
ballgame.
- analyze_media_age.py: stop asserting the unsupported verdict; say what
the number does and does not show, and point at the probe.
One signal there is immune to the confound and survives: 2026-07-09 kept
38 images and lost 12. Same conversation, same day, opposite outcomes —
no retention policy does that, so at least part of this is per-asset.
"Do I have to export within N days?" is answerable from the exports
already on disk — the renderer records every image's outcome inline
( when saved, a placeholder when not) and the
conversation date is in the filename. Group by month and source and the
hypotheses separate: a clean old/new cutoff means expiry, user_upload
dying at an age model_generated survives means the source matters, and
losses scattered through months that otherwise downloaded fine means
neither.
Offline, no token, no API calls.
JesseMarkowitz