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		<title>PROBE benchmark exposes gaps in AI protein-function annotation</title>
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				<category><![CDATA[Biology]]></category>
		<category><![CDATA[annotation accuracy]]></category>
		<category><![CDATA[Bioinformatics]]></category>
		<category><![CDATA[computational biology]]></category>
		<category><![CDATA[Gene Ontology]]></category>
		<category><![CDATA[Large Language Models]]></category>
		<category><![CDATA[multi-organism]]></category>
		<category><![CDATA[probe]]></category>
		<category><![CDATA[PROBE benchmark]]></category>
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		<category><![CDATA[protein function]]></category>
		<category><![CDATA[semantic similarity]]></category>
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					<description><![CDATA[A 1,000-protein, five-organism benchmark found that leading open-source language models showed biological semantic alignment but achieved a best macro-F1 of only 9.3% for exact Gene Ontology protein-function annotation.]]></description>
		
		
		
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