A small tool to view real-world ActivityPub objects as JSON! Enter a URL
or username from Mastodon or a similar service below, and we'll send a
request with
the right
Accept
header
to the server to view the underlying object.
{
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{
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"inReplyToAtomUri": "ostatus:inReplyToAtomUri",
"conversation": "ostatus:conversation",
"sensitive": "as:sensitive",
"toot": "http://joinmastodon.org/ns#",
"votersCount": "toot:votersCount",
"blurhash": "toot:blurhash",
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"type": "Note",
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"published": "2024-01-20T13:24:42Z",
"url": "https://mastodon.social/@MatteoCarandini/111788496141120995",
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"content": "<p>All models are wrong, but some are more useful than others. When describing sensory decisions, logistic classification is often more useful:</p><p>- it is trivial to add predictors, both sensory and non-sensory; <br />- it has a simple linear interpretation in terms of log odds; <br />- it is great at describing the effects of brain manipulations.</p><p>Also:<br />- it comes straight out of probability theory;<br />- it incorporates the Bayesian assumption from the get-go; <br />- it is easily extended to multiple alternatives.</p>",
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"en": "<p>All models are wrong, but some are more useful than others. When describing sensory decisions, logistic classification is often more useful:</p><p>- it is trivial to add predictors, both sensory and non-sensory; <br />- it has a simple linear interpretation in terms of log odds; <br />- it is great at describing the effects of brain manipulations.</p><p>Also:<br />- it comes straight out of probability theory;<br />- it incorporates the Bayesian assumption from the get-go; <br />- it is easily extended to multiple alternatives.</p>"
},
"updated": "2024-01-21T13:24:53Z",
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"url": "https://files.mastodon.social/media_attachments/files/111/794/124/861/923/597/original/b3cb3020f0aa202e.png",
"name": "Examples of psychometric curves fitted by the logistic classification model, showing data from the @internationalbrainlab@mastodon.world, from @ArminLak@neuromatch.social, and from the Churchland lab.",
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