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User:ClueBot NG

ClueBot NG
This user is a bot
( · )
US Air Force 021105-O-9999G-001 Spirit in the blue sky.jpg
ClueBot NG aids in Operation Enduring Encyclopedia.
Operator Cobi , Crispy1989 (more info)
Approved? Yes, BRFA.
Flagged? Yes.
Task(s) Reverting vandalism.
Edit rate Over 9,000 EPM.
Edit period(s) Continually
Automatic or manual? Automatic
Programming language(s) C, C++, PHP, Python, Bash, and Java (more info)
Exclusion compliant? Yes
Emergency shutoff-compliant? Yes
Other information




Administrators may turn the bot off by changing this page to 'False'.

This bot is an .

ClueBot NG is an anti-vandal bot that tries to detect and revert vandalism quickly and automatically.

Special thanks to:

Questions, comments, contributions, and suggestions regarding:

ClueBot NG's development and discussion about internals takes place almost entirely on its IRC channel. The IRC channel can be accessed on irc.cluenet.org channel #cluebotng. Please join if you have any detailed questions about the internals or would like to speak real-time with the developers.

Bots in #cluebotng that may be useful are:

For the bot to be effective, the dataset needs to be expanded. Our current dataset has some degree of bias, as well as some inaccuracies. We need volunteers to help review edits and classify them as either vandalism or constructive. We hope to eventually completely replace our current dataset with a random sampling of edits, reviewed and classified by volunteers. More thorough instructions on how to use the interface, and the interface itself, are at the dataset review interface (currently broken).

Extended statistics on contributors, including edit review counts and accuracy, are available here.

For those that help with and contribute to the review interface, a user box is available for you:



Use it with: {{User:ClueBot NG/Review User Box}}

As ClueBot-NG requires a dataset to function, the dataset can also be used to give fairly accurate statistics on its accuracy and operation. Different parts of the dataset are used for training and trialing, so these statistics are not biased.

The exact statistics change and improve frequently as we update the bot. Currently:

Currently, the trial dataset used to generate these statistics is a random sampling of edits, each reviewed by at least two humans, so statistics are accurate.

Note: These statistics are calculated before post-processing filters. Post-processing filters primarily reduce false positive rate (ie, the actual number of false positives will be less than stated here), but can also slightly reduce catch rate.

See the FAQ.


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