ActivityPub Viewer

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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{ "@context": [ "https://www.w3.org/ns/activitystreams", { "ostatus": "http://ostatus.org#", "atomUri": "ostatus:atomUri", "inReplyToAtomUri": "ostatus:inReplyToAtomUri", "conversation": "ostatus:conversation", "sensitive": "as:sensitive", "toot": "http://joinmastodon.org/ns#", "votersCount": "toot:votersCount", "blurhash": "toot:blurhash", "focalPoint": { "@container": "@list", "@id": "toot:focalPoint" }, "Hashtag": "as:Hashtag", "Emoji": "toot:Emoji" } ], "id": "https://mstdn.science/users/serhii/statuses/112671904844311439", "type": "Note", "summary": null, "inReplyTo": null, "published": "2024-06-24T13:47:09Z", "url": "https://mstdn.science/@serhii/112671904844311439", "attributedTo": "https://mstdn.science/users/serhii", "to": [ "https://www.w3.org/ns/activitystreams#Public" ], "cc": [ "https://mstdn.science/users/serhii/followers" ], "sensitive": false, "atomUri": "https://mstdn.science/users/serhii/statuses/112671904844311439", "inReplyToAtomUri": null, "conversation": "tag:mstdn.science,2024-06-24:objectId=53949295:objectType=Conversation", "content": "<p>Have government measures to combat <a href=\"https://mstdn.science/tags/COVID19\" class=\"mention hashtag\" rel=\"tag\">#<span>COVID19</span></a> had any effect? The researchers used multiverse analyses, analysed daily data on 16 government measures in 181 countries and built, 99736 analytical models:</p><p>:doi: <a href=\"https://doi.org/10.1126/sciadv.adn0671\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" translate=\"no\"><span class=\"invisible\">https://</span><span class=\"\">doi.org/10.1126/sciadv.adn0671</span><span class=\"invisible\"></span></a> </p><p>The result is that the authors found no evidence that government measures have helped contain COVID-19. Have a look at the figure – it&#39;s not even zero, but rather a little bit of damage!</p><p><a href=\"https://mstdn.science/tags/government\" class=\"mention hashtag\" rel=\"tag\">#<span>government</span></a> <a href=\"https://mstdn.science/tags/responses\" class=\"mention hashtag\" rel=\"tag\">#<span>responses</span></a> <a href=\"https://mstdn.science/tags/pandemic\" class=\"mention hashtag\" rel=\"tag\">#<span>pandemic</span></a> <a href=\"https://mstdn.science/tags/politics\" class=\"mention hashtag\" rel=\"tag\">#<span>politics</span></a> <a href=\"https://mstdn.science/tags/losers\" class=\"mention hashtag\" rel=\"tag\">#<span>losers</span></a></p>", "contentMap": { "uk": "<p>Have government measures to combat <a href=\"https://mstdn.science/tags/COVID19\" class=\"mention hashtag\" rel=\"tag\">#<span>COVID19</span></a> had any effect? The researchers used multiverse analyses, analysed daily data on 16 government measures in 181 countries and built, 99736 analytical models:</p><p>:doi: <a href=\"https://doi.org/10.1126/sciadv.adn0671\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" translate=\"no\"><span class=\"invisible\">https://</span><span class=\"\">doi.org/10.1126/sciadv.adn0671</span><span class=\"invisible\"></span></a> </p><p>The result is that the authors found no evidence that government measures have helped contain COVID-19. Have a look at the figure – it&#39;s not even zero, but rather a little bit of damage!</p><p><a href=\"https://mstdn.science/tags/government\" class=\"mention hashtag\" rel=\"tag\">#<span>government</span></a> <a href=\"https://mstdn.science/tags/responses\" class=\"mention hashtag\" rel=\"tag\">#<span>responses</span></a> <a href=\"https://mstdn.science/tags/pandemic\" class=\"mention hashtag\" rel=\"tag\">#<span>pandemic</span></a> <a href=\"https://mstdn.science/tags/politics\" class=\"mention hashtag\" rel=\"tag\">#<span>politics</span></a> <a href=\"https://mstdn.science/tags/losers\" class=\"mention hashtag\" rel=\"tag\">#<span>losers</span></a></p>" }, "attachment": [ { "type": "Document", "mediaType": "image/jpeg", "url": "https://static.mstdn.science/media_attachments/files/112/671/897/664/532/692/original/c007506ef4785c26.jpg", "name": "Distribution of standardized effect sizes for all analyses and selected groups.\n\nThe t-statistics are used as a proxy for the standardized effect size of different models. The count of models with t-statistics in each interval [x, x + 0.25) for x ranging from −20 to +20 is shown in each panel (intervals with 0 models are not shown). The portion of the models that are significant using the false discovery rate is represented by the shade. In (A), for example, the t-statistic interval with the largest count of models is between 0.75 and 1.00. None of those models are significant. Panel (A) includes all models; (B) includes models for the year 2020; (C) includes models with the stringency index as the predictor; (D) includes models with cases as the outcome; (E) includes models designed to assess the relationship between the policy level and the outcome level (model 1); and panel (F) includes models designed to assess the relationship between the policy level and the change (growth) in the outcome (model 4).\n\nBendavid, E., & Patel, C. J. (2024). Epidemic outcomes following government responses to COVID-19: Insights from nearly 100,000 models. Science Advances, 10(23). https://doi.org/10.1126/sciadv.adn0671\n", "blurhash": "U0S~#CxuE0s;~qjuozazRjbHoLRj~qofayRj", "focalPoint": [ -0.44, 0.72 ], "width": 2801, "height": 2961 } ], "tag": [ { "type": "Hashtag", "href": "https://mstdn.science/tags/COVID19", "name": "#COVID19" }, { "type": "Hashtag", "href": "https://mstdn.science/tags/government", "name": "#government" }, { "type": "Hashtag", "href": "https://mstdn.science/tags/responses", "name": "#responses" }, { "type": "Hashtag", "href": "https://mstdn.science/tags/pandemic", "name": "#pandemic" }, { "type": "Hashtag", "href": "https://mstdn.science/tags/politics", "name": "#politics" }, { "type": "Hashtag", "href": "https://mstdn.science/tags/losers", "name": "#losers" }, { "id": "https://mstdn.science/emojis/9143", "type": "Emoji", "name": ":doi:", "updated": "2022-11-11T14:35:22Z", "icon": { "type": "Image", "mediaType": "image/png", "url": "https://static.mstdn.science/custom_emojis/images/000/009/143/original/581a8e7d757b39a1.png" } } ], "replies": { "id": "https://mstdn.science/users/serhii/statuses/112671904844311439/replies", "type": "Collection", "first": { "type": "CollectionPage", "next": "https://mstdn.science/users/serhii/statuses/112671904844311439/replies?only_other_accounts=true&page=true", "partOf": "https://mstdn.science/users/serhii/statuses/112671904844311439/replies", "items": [] } }, "likes": { "id": "https://mstdn.science/users/serhii/statuses/112671904844311439/likes", "type": "Collection", "totalItems": 3 }, "shares": { "id": "https://mstdn.science/users/serhii/statuses/112671904844311439/shares", "type": "Collection", "totalItems": 1 } }