Script X-ray

Where viewers went back to watch a video again. YouTube publishes a Most replayed graph for its videos, and Prepublish keeps that graph beside the caption timings for every video it reads. Each video has a transcript page showing the graph and the moments viewers returned to, with what was said at each. This page shows what the corpus holds and how the model that ranks passages is measured.

The graph counts replays. It does not show where viewers stopped watching. Every association below is measured across public videos, and an association is not a cause.

The model trains once 30 videos from 5 channels can be held out for testing. The corpus holds 73 videos today.

Training runs

Every run, newest first. A run is promoted only when it ranks passages on channels it never saw at least as well as the model already in use.

No run has finished yet, so the corpus has no model to show.

The corpus

One row per passage of a video whose replay graph was read and whose caption timings could be aligned to its own words.

Videos

73

Channels

42

Passages

2,016

Holding a peak

215

Recent X-rays

The videos read most recently, newest first. Each one has its own page at /youtube-transcript/<videoId>.

How it works

  1. 1

    Every transcript read keeps YouTube's public Most replayed graph and the caption cue timings beside the words.

  2. 2

    Each passage of a video with a graph is given the replay level over its own span, and the answers to a fixed set of questions about what the passage does.

  3. 3

    A nightly run fits a model on the corpus and measures it on channels kept out of training, against a model that knows only where in a video a passage sits.

  4. 4

    A new model replaces the one in use only when it ranks passages on channels it never saw at least as well as the model already in use.

Questions

Does this predict retention?

No. The graph behind Script X-ray counts replays: how often a moment was watched again. It is not a record of how many viewers stayed with the video, and a model trained on it cannot tell you where viewers stopped watching. What it estimates is replay potential, which is how closely a passage resembles passages viewers chose to watch twice.

Why do some videos have no X-ray?

YouTube publishes a Most replayed graph only once a video has enough views. Below that there is nothing to read, and the transcript page says so in one line rather than showing an empty chart.

Where do the numbers come from?

From YouTube’s public Most replayed graph and the public caption timings of videos that have both. Nothing comes from a creator’s private analytics, and no creator’s studio data is read.

How is the model measured?

On channels kept out of training entirely. Every figure on this page is measured there, and it is measured against the same model with the position of a passage alone, which is the honest baseline: passages near the start of a video are replayed more often than passages near the end.

When does replay evidence appear on an audit?

Once the model in use clears the bar: its ranking of held-out passages has to beat position alone with a confidence interval above zero. Until then an audit does not show it, because an estimate that is no better than knowing where a passage sits is not worth acting on.

Find the moments in your own script

Paste a draft and the check reads it before you record: hook strength, pacing, and the passages most likely to lose viewers, with copy-paste rewrites.

Check a script freeRead a video transcript