# 7. Geometry

## 7.1 Page fingerprints

Several publishers stamp each download with the institution, date and time, so two copies of one paper rarely share a SHA-256.
Every page of a witness therefore also has a fingerprint, `scienting-page/1`.
Geometry and digitizations point at fingerprints, so a re-download keeps every box and every digitization.

The input is the page's size after rotation, its text-layer lines in content-stream order (each a string and, where known, a box), and the SHA-256 of each embedded image's stream data as stored.
To compute the fingerprint:

1. Remove every line that a stamp rule matches ([7.2](#72-stamp-rules)).
2. Join the remaining lines with U+0020.
3. Delete every whitespace character and every character of General Category Cc or Cf.
4. Fold Unicode script characters and dashes before digits as the strict projection does for text ([5.4](05-hashes.md#54-simple-notation)), then apply NFKC.
5. Round the width and height to whole points, half up.
6. The fingerprint is SHA-256 of the canonical JSON of `{"format": "scienting-page/1", "size": [width, height], "text": the text, "images": the image hashes, sorted}`.

Whitespace is deleted rather than collapsed because text extractors disagree about where they insert spaces, and it is deleted before folding so that "10 -20" and "10-20" fold alike.
A scanned page with no text layer is fingerprinted by its size and its images alone.
Two witnesses whose fingerprints are equal, page for page, are the same edition of the paper.

How lines are extracted from a PDF is outside this text; the vectors give the lines, so implementations are tested on the function.
`fingerprints.jsonl` gives two differently stamped downloads of one ACS-style page and of one Wiley-style page that share their fingerprints, a page with one changed digit that does not, and a scan.

## 7.2 Stamp rules

Stamp rules are published in `scienting-stamps/1` files.
Each rule has an `id`, a `pattern`, a `where` (`any`, or `margin` with a `margin` in points, default 36) and a note.
A rule matches a line when its pattern is found in the line's normalized text, with ASCII letters compared without case; a `margin` rule matches only lines whose box lies wholly within the margin of one edge.
Patterns use only syntax that ECMAScript and Python read alike: literals, `.`, `*`, `+`, `?`, `^`, `$`, classes and escaped punctuation.

[registry/stamps/scienting-stamps-1.json](../registry/stamps/scienting-stamps-1.json) holds the published rules.
A team adds rules it learns, when two witnesses of one version differ only in such lines, in files of its own with `learned: true`.
A missed stamp splits one edition into two; an over-broad rule hides a real difference.

## 7.3 `pages.jsonl`

| Property | Holds |
| --- | --- |
| `witness` | The witness ID. |
| `page` | The page number in the witness, from 1. |
| `page_fp` | The fingerprint. |
| `size` | `[width, height]` in points, after rotation. |
| `page_label` | The printed page label, when there is one. |
| `text_layer` | Whether the page has a text layer. |
| `stamps_removed` | The IDs of the rules that removed lines, in line order, when any did. |

Pages sort by witness ID, then page.

## 7.4 `locations.jsonl`

| Property | Holds |
| --- | --- |
| `node` | The node ID. |
| `page_fp` | The page's fingerprint, which some page of some witness has. |
| `page` | The page number. |
| `page_label` | The printed label. |
| `boxes` | One or more `[x0, y0, x1, y1]` in PDF points, origin at the top left after rotation. |
| `approx` | `true` when the boxes come from OCR line boxes rather than glyphs. |

A node has one record per page it appears on; a sentence that wraps has several boxes.
Locations sort by the node's position in document order, then page, then fingerprint.
Because locations point at fingerprinted pages, a reader can rebuild a document from its own download: it fingerprints the pages, finds the matching ones and reads the text at the stored boxes.