# Crossref Works: Scholarly Metadata, DOIs and Retractions (`cprussin/crossref-works`) Actor
Scholarly article metadata from Crossref: DOI, title, authors with ORCID and ROR, journal, ISSN, publisher, dates, citation counts, funders, licences, full-text links. Filter by query, ISSN, member, type, date; daily new-works and retraction feeds. $1 per 1,000 works.
- **URL**: https://apify.com/cprussin/crossref-works.md
- **Developed by:** [Connor Prussin](https://apify.com/cprussin) (community)
- **Categories:** Education, AI
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $1.00 / 1,000 works
This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event
## What's an Apify Actor?
An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.
## How to integrate an Actor?
If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.
For examples already wired to this Actor's own input schema, see the [API](#api) section below.
Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).
# README
## Crossref Works: Scholarly Article Metadata, DOIs and Retractions API
**Crossref Works** exports metadata of scholarly works (journal articles, preprints, book chapters, conference papers, datasets) registered with **Crossref**, the DOI agency behind 170M+ research outputs, as clean JSON, CSV or Excel. It reads the official, keyless [Crossref REST API](https://api.crossref.org) at its published rate limits. No login, no API key, no browser, no proxy.
- ✅ **Search by text, author, publisher**, or filter by **journal ISSN**, **Crossref member** (publisher), **work type**, **funder** and **date** (published, created, deposited, indexed).
- ✅ **Rich records**: DOI, title, authors with **ORCID** and affiliations (**ROR**), journal and ISSNs, publisher, publication dates, volume/issue/pages, **citation count**, references count, **funders and award numbers**, **licences** and **full-text links**.
- ✅ **New since last run**: every work registered on each full day since your previous run, without overlaps. Schedule it daily for a new-publications feed.
- ✅ **Retraction feed**: retraction notices with the DOIs they retract; any work carries `isRetracted` when a retraction notice updates it.
- ✅ **No abstracts**: abstracts are the publishers' copyright, so they are never requested.
### Start in one minute
Click **Start** with the prefilled input:
```json
{
"mode": "search",
"query": "large language models",
"types": ["journal-article"],
"fromDate": "2026-10-01",
"untilDate": "2026-10-31",
"maxItems": 20
}
```
You get: the 20 most relevant journal articles about large language models published in October 2026, with `doi`, `title`, `authors`, `containerTitle`, `publisher`, `publishedDate`, `citedByCount` and `licenses`.
**Cost:** $0.02: 20 works × $0.001, plus the $0.00005 actor-start fee.
### Use with an AI assistant
Connect the [Apify MCP server](https://mcp.apify.com) to Claude, ChatGPT, Cursor or any MCP client (`https://mcp.apify.com?tools=cprussin/crossref-works` loads only this actor), then paste:
```text
Use the Apify actor cprussin/crossref-works to list papers retracted in the last week, with the retraction notice, the retracted DOI, journal and publisher.
```
### Recipes
#### Daily retraction watch (scheduled task)
The first run covers yesterday; every later run covers the full days since the previous run.
```json
{
"mode": "retractions",
"maxItems": 5000
}
```
#### New articles in your journals every day
```json
{
"mode": "newSince",
"issns": ["1476-4687", "0036-8075"],
"maxItems": 1000
}
```
#### Everything a publisher published last month
```json
{
"mode": "search",
"memberIds": ["1968"],
"types": ["journal-article"],
"fromDate": "2026-10-01",
"untilDate": "2026-10-31",
"maxItems": 10000
}
```
#### Most-cited NSF-funded papers of 2025
```json
{
"mode": "search",
"funderIds": ["100000001"],
"fromDate": "2025",
"untilDate": "2025",
"sort": "is-referenced-by-count",
"maxItems": 100
}
```
### What can you do with Crossref data?
- **Research offices and librarians**: track every new paper in your journals or from your funder.
- **Research-integrity teams and journalists**: monitor retractions daily and check reference lists against retracted DOIs.
- **Publishers and analysts**: benchmark output, citations, licences and open-access share by publisher or journal.
- **AI and search builders**: feed clean bibliographic metadata into RAG, recommender or citation tools.
### Input
| Field | Description | Example |
| ----------------------------------------- | ----------------------------------------------------------- | --------------------- |
| `mode` | `search`, `newSince` or `retractions` | `"retractions"` |
| `query` / `queryAuthor` / `publisherName` | Free text, author name, publisher name | `"crispr"` |
| `issns` | Journal ISSNs | `["1476-4687"]` |
| `memberIds` | Crossref member IDs (publishers) | `["78"]` |
| `types` | Work types | `["journal-article"]` |
| `funderIds` | Open Funder Registry IDs | `["100000001"]` |
| `fromDate` / `untilDate` | Date range (YYYY-MM-DD, YYYY-MM or YYYY) | `"2026-10-01"` |
| `dateField` | `published`, `created`, `deposited` or `indexed` | `"created"` |
| `sort` / `order` | e.g. `is-referenced-by-count`, `published`; `desc` or `asc` | `"published"` |
| `maxItems` | Max works (default 100) | `1000` |
| `contactEmail` | Optional: your email, for Crossref's faster polite pool | `"you@example.org"` |
### What data do you get for each work?
```json
{
"doi": "10.1155/ijce/9891504",
"url": "https://doi.org/10.1155/ijce/9891504",
"title": "RETRACTION: Analysis of Bagasse Cellulose‐Based Hydrogel for Methylene Blue Removal from Textile Industry Wastewater",
"subtitle": null,
"type": "journal-article",
"authors": [
{
"given": "International Journal of",
"family": "Chemical Engineering",
"name": null,
"orcid": null,
"sequence": "first",
"affiliations": []
}
],
"authorNames": ["International Journal of Chemical Engineering"],
"containerTitle": "International Journal of Chemical Engineering",
"shortContainerTitle": "International Journal of Chemical Engineering",
"issns": ["1687-806X", "1687-8078"],
"issnPrint": "1687-806X",
"issnElectronic": "1687-8078",
"isbns": [],
"publisher": "Wiley",
"memberId": "311",
"prefix": "10.1155",
"publishedDate": "2026-01",
"publishedPrintDate": "2026-01",
"publishedOnlineDate": "2026-11-01",
"createdAt": "2026-11-01T09:51:42Z",
"depositedAt": "2026-11-01T23:46:57Z",
"indexedAt": "2026-11-02T00:26:28Z",
"volume": "2026",
"issue": "1",
"page": null,
"articleNumber": "9891504",
"subjects": [],
"referencesCount": 1,
"citedByCount": 0,
"funders": [],
"licenses": [
{
"url": "https://creativecommons.org/licenses/by/4.0/",
"start": "2026-11-01",
"contentVersion": "vor",
"delayInDays": 304
},
{
"url": "http://doi.wiley.com/10.1002/tdm_license_1.1",
"start": "2026-01-01",
"contentVersion": "tdm",
"delayInDays": 0
}
],
"fullTextLinks": [
{
"url": "https://onlinelibrary.wiley.com/doi/pdf/10.1155/ijce/9891504",
"contentType": "application/pdf",
"contentVersion": "vor",
"intendedApplication": "text-mining"
},
{
"url": "https://onlinelibrary.wiley.com/doi/full-xml/10.1155/ijce/9891504",
"contentType": "application/xml",
"contentVersion": "vor",
"intendedApplication": "text-mining"
},
{
"url": "https://onlinelibrary.wiley.com/doi/pdf/10.1155/ijce/9891504",
"contentType": "unspecified",
"contentVersion": "vor",
"intendedApplication": "similarity-checking"
}
],
"updateTo": [
{
"doi": "10.1155/2023/2313874",
"type": "retraction",
"label": "Retraction",
"source": "publisher",
"date": "2026-11-01"
}
],
"updatedBy": [],
"retractedDois": ["10.1155/2023/2313874"],
"isRetracted": false,
"updatePolicy": "https://doi.org/10.1002/crossmark_policy",
"scrapedAt": "2026-11-02T12:00:00.000Z"
}
```
Titles are plain text (JATS/HTML markup removed). Abstracts and reference lists are not exported.
### How much does it cost to get Crossref metadata?
Pay per event:
- **$0.001 per work** ($1 per 1,000).
- $0.00005 per run start. Platform compute is included.
- A tracked run with no new full day since the last run outputs nothing and costs only the start fee.
### FAQ
**Is this legal?** Yes. Crossref states that almost all of its metadata is reusable without restriction, except abstracts, which this actor never requests; bibliographic facts are not subject to copyright and Crossref-generated data is CC0. See [Crossref's metadata licensing](https://www.crossref.org/documentation/retrieve-metadata/). The actor uses the public API, identifies itself, sends one request at a time and follows the rate limit Crossref advertises (never more than 3 requests per second).
**Do I need a Crossref account or key?** No. Optionally give `contactEmail`: Crossref then serves you from its faster "polite" pool. Without it the public pool allows about one request per second; each request returns up to 1,000 works.
**How does "since last run" work?** In `newSince` and `retractions` modes without `fromDate`, each run covers the full UTC days after the previous run's last day, up to yesterday. The last day is stored in a named key-value store in your Apify account (`crossref-works-state`), one per filter set. If a run stops early (max items or max charge), the next run starts from the same day again.
**Why retraction notices and not retracted papers?** Crossref records retractions as notices that point to the retracted work (`retractedDois`). Any work you fetch also shows `isRetracted` when such a notice exists.
**How many works are there per day?** Typically 20,000-40,000 new DOIs a day across all types, and tens to a few hundred retraction notices.
### Related actors
- [Document to Markdown](https://apify.com/cprussin/document-to-markdown): turn PDFs and other documents (e.g. open-access full texts) into clean Markdown.
- [Substack Scraper](https://apify.com/cprussin/substack-scraper): newsletter posts and metadata from Substack.
# Actor input Schema
## `mode` (type: `string`):
Search: works matching the query and filters. New since last run: works registered (created) on each full UTC day since this actor's previous run with the same filters (yesterday on the first run). Retractions: retraction notices (update-type:retraction), tracked since the last run like New, or for a date range.
## `query` (type: `string`):
Free text matched against titles, authors, journals and other metadata, e.g. large language models. Results are sorted by relevance unless you set Sort.
## `queryAuthor` (type: `string`):
Author name to match, e.g. Jennifer Doudna.
## `publisherName` (type: `string`):
Publisher name to match, e.g. Elsevier. For an exact publisher use Member IDs.
## `issns` (type: `array`):
Print or electronic ISSNs, e.g. 1476-4687 (Nature). Works in any listed journal match.
## `memberIds` (type: `array`):
Publisher member IDs, e.g. 78 (Elsevier), 297 (Springer Nature), 311 (Wiley), 1968 (MDPI). Find one at api.crossref.org/members?query=name.
## `types` (type: `array`):
Crossref work types. Leave empty for all.
## `funderIds` (type: `array`):
Open Funder Registry IDs, e.g. 100000001 (NSF) or 10.13039/501100000780 (European Commission).
## `fromDate` (type: `string`):
First date (inclusive) of the Date field: YYYY-MM-DD, YYYY-MM or YYYY. In New and Retractions modes, setting it turns off since-last-run tracking.
## `untilDate` (type: `string`):
Last date (inclusive) of the Date field. Same formats.
## `dateField` (type: `string`):
Which date the range applies to. Default: published (Search) or created, i.e. DOI registered (New, Retractions). Deposited/indexed also catch re-deposited older works.
## `sort` (type: `string`):
Sort order. Default: relevance with search text, otherwise Crossref's order.
## `order` (type: `string`):
Sort direction.
## `maxItems` (type: `integer`):
Stop after this many works. Each work is billed once. In tracked modes the next run only moves on when every work was output.
## `contactEmail` (type: `string`):
Crossref asks API users to identify themselves; with an email the requests are sent with mailto= and use Crossref's faster polite pool. Sent only to Crossref.
## Actor input object example
```json
{
"mode": "search",
"query": "large language models",
"types": [
"journal-article"
],
"fromDate": "2026-10-01",
"untilDate": "2026-10-31",
"order": "desc",
"maxItems": 20
}
```
# Actor output Schema
## `results` (type: `string`):
No description
# API
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'apify-client';
// Initialize the ApifyClient with your Apify API token
// Replace the '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"mode": "search",
"query": "large language models",
"types": [
"journal-article"
],
"fromDate": "2026-10-01",
"untilDate": "2026-10-31",
"maxItems": 20
};
// Run the Actor and wait for it to finish
const run = await client.actor("cprussin/crossref-works").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs
```
## Python example
```python
from apify_client import ApifyClient
# Initialize the ApifyClient with your Apify API token
# Replace '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"mode": "search",
"query": "large language models",
"types": ["journal-article"],
"fromDate": "2026-10-01",
"untilDate": "2026-10-31",
"maxItems": 20,
}
# Run the Actor and wait for it to finish
run = client.actor("cprussin/crossref-works").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"mode": "search",
"query": "large language models",
"types": [
"journal-article"
],
"fromDate": "2026-10-01",
"untilDate": "2026-10-31",
"maxItems": 20
}' |
apify call cprussin/crossref-works --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"type": "http",
"url": "https://mcp.apify.com/?tools=fetch-actor-details,cprussin/crossref-works"
}
}
}
```
The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).
## OpenAPI specification
Download the OpenAPI definition: https://api.apify.com/v2/actors/vh1NIoQizh0KUM0kv/builds/8NqdsAPWzBFSVuXmj/openapi.json