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Summary

DescriptionAdoration by the shepherds animated.gif	English: Animation of the Adoration by the Shepherds of Gerard van Honthorst (1622)
Date	1622
Source	https://www.arguments.es/liturgia/la-natividad-en-la-pintura-artecristiano/
Author	By Meta AI based on painting Adoration by the shepards of Gerard van Honthorst in 1622.

Licensing

	This work is in the public domain in its country of origin and other countries and areas where the copyright term is the author's life plus 70 years or fewer. Category:PD-old missing SDC copyright status You must also include a United States public domain tag to indicate why this work is in the public domain in the United States. Note that a few countries have copyright terms longer than 70 years: Mexico has 100 years, Jamaica has 95 years, Colombia has 80 years, and Guatemala and Samoa have 75 years. This image may not be in the public domain in these countries, which moreover do not implement the rule of the shorter term. Honduras has a general copyright term of 75 years, but it does implement the rule of the shorter term. Copyright may extend on works created by French who died for France in World War II (more information), Russians who served in the Eastern Front of World War II (known as the Great Patriotic War in Russia) and posthumously rehabilitated victims of Soviet repressions (more information). Category:PD-old missing SDC copyright status
	This file has been identified as being free of known restrictions under copyright law, including all related and neighboring rights.

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Category:CC-PD-Mark Category:Author died more than 70 years ago public domain images Category:PD-old missing SDC copyright status

This file is in the public domain because it is the work of a computer algorithm or artificial intelligence and does not contain sufficient human authorship to support a copyright claim.

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Most image-generating AI models were trained using works that are protected by copyright. In some cases, such models can output content with major copyrightable image elements which are identical to or derivative of the original training data, making these outputs derivative works. Accordingly, there is a risk that AI-generated media uploaded on Commons may violate the rights of the authors of the original works. See Commons:AI-generated media for additional details.

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