extract_references()

Find the DOIs that the seed papers cite, in one PDF or in every PDF in a folder.

extract_references(
    source: str,
    save: str | None = None,
    cache: bool = True,
) -> list[dict]

Source: theoryminer/prepare/dois.py

The function reads every page of each seed paper and finds each DOI. It repairs a DOI that the PDF cut at a line end (“10.1007/s1096 4-015-0354-5”). It leaves out the DOI of the seed itself and the DOIs of its parts (figures, tables). A reference that prints no DOI cannot be found. A bad file does not stop the run: the summary names it. It writes a CSV file only when you give save.

Arguments

`source`

The seed paper, or the folder of seed papers, to read.

Values: the path of one PDF file, or the path of a folder. The function looks in the folder only, not in its subfolders.
Default: none. Give a path.

`save`

Where to write the rows as a CSV file, with the columns doi, n_seeds, cited_by. A download tool can read its “doi” column.

Values: None, a path that ends with “.csv”, or a folder (then <folder>/references.csv). A missing folder is made.
Default None: write no file.

`cache`

Whether to use the page cache <pdf>.pages.json beside each PDF.

Values: True or False.
Default True: read the cache when it exists, else read the PDF and write the cache. False reads every PDF again and writes no cache.

Returns

A list of dicts, one per unique reference DOI, with the keys

key	meaning
`doi`	the DOI, in lowercase
`n_seeds`	the number of seed papers that cite it
`cited_by`	the doc_ids of those seed papers

The DOIs that most seeds cite come first.

Raises

ValueError: The source does not exist, or the folder has no PDF.

Example

>>> refs = extract_references("sample_files")
>>> refs[0]["doi"], refs[0]["n_seeds"]
('10.1037/0003-066x.55.1.68', 2)

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