Any tool can print a timestamp
Every short form analysis tool will hand you a list of moments. The trouble is that the list looks identical whether the tool actually read your video or simply produced timestamps that feel about right for something of that length. From the outside there is no way to tell, and that is true of ours as much as anyone else's.
That is an uncomfortable position for a product whose entire output is a set of moments. So instead of asserting that ours are real, we built a test that could have shown they were not, and we ran it.
The question we set out to answer
Retensis flags specific points on your timeline. The question worth answering is whether those points are anchored to the structure of the video, or whether the same list could have come from anywhere.
Structure here means the edit itself: the cuts, the places where one shot becomes another, the decisions you made in the timeline. A tool that is genuinely reading a video should land near those decisions more often than a tool that is not. If it does not, the output is decoration.
How we checked it
We measured how far each flagged moment sits from the nearest cut in the edit, and compared that distance against two independent baselines that stand in for chance.
Using a single baseline would have been weak. A result can clear one and still be an artefact of how a particular video happens to be cut, or of nothing more than the length of the video. The two baselines test those explanations separately, so clearing both rules out both.
Everything that decides the outcome was fixed before the run: both baselines, the sample, and the thresholds for calling the result either way. That matters more than it sounds. A test designed after the results are in can always be made to pass, and a number produced that way is worth nothing. This one could have failed.
The full method and the complete figures are published in how we validate drop-off detection.
What the result shows
It cleared both baselines, and not marginally.
What follows from that is specific and worth stating plainly: the moments Retensis flags are tied to the structure of your edit. They are not spread at random, and they are not generic points that would fit any video of that length, because those are precisely the two things the baselines represent.
The practical consequence is that a flagged moment is worth opening. It points at a real decision in your edit, so the timestamp is somewhere to look rather than something to take on trust. That is a smaller claim than most tools in this category make, and unlike most of them, it is one we can show you the working for.
The numbers
A lower distance is a better result, since it means the flagged moments sit closer to real cuts. The two baseline rows carry the probability that chance alone would produce a result that good.
| Measured | Result |
|---|---|
| Flagged moments measured | 497 |
| Median distance to nearest cut | 0.83s |
| Baseline 1, moments rearranged | 1.07s, about 1 in 900 |
| Baseline 2, moments from elsewhere | 1.13s, about 1 in 5,000 |
| Within half a second of a cut | 37.4% |
| Within one second of a cut | 53.7% |
Frequently asked questions
We measured them. For every flagged moment we checked how far it sits from the nearest cut in the edit, then compared that against two independent baselines standing in for chance. Both baselines were fixed before the run, so the test could have failed. It did not: the flagged moments land closer to real cuts than either baseline, and the odds of chance producing a result that good are about 1 in 900 against the first and about 1 in 5,000 against the second.
Because beating one baseline can be an artefact rather than a finding. A result can look strong simply because of how a particular video happens to be cut, or because moments placed anywhere in a video of that length would have scored similarly. The two baselines test those two different explanations, so clearing both rules out both. Most published claims about this kind of tool clear neither, because most are never tested at all.
That something happens there worth looking at. The measurement shows these moments are tied to the structure of your edit rather than scattered across it, so the timestamp is a place to open and review rather than a number to accept on faith. It points you at a decision you made while cutting, which is the part you can change next time.
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