#false_positive
Live, measured metrics for the hashtag #false_positive from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #false_positive
This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.
Day-by-day usage
measured · fosstodon.org (Mastodon public tags API) · fetched 2026-08-24 04:13 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · fosstodon.org (Mastodon public search API) · fetched 2026-08-24 04:13 UTCLive pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-08-24 04:13 UTCEverything below is measured over the latest 11 public posts (spanning ~49694 hours).
Posting hours (UTC)
Languages: Russian (9) · English (2)
Avg boosts / post: 0.1
Top of the latest posts
Probe-сеть из 10 регионов: что я не учёл про AS-разнесённость Я делаю Valpero — uptime-мониторинг с проверками из 10 регионов мира. Когда я только собирал probe-сеть, я был уверен, что 10 географических точек это автоматически и 10 точек от
Multi-region quorum: «все регионы согласны» против «N из M» К-of-N или all-must-agree? Два подхода к quorum-логике в multi-region мониторинге. Я остановился на all-must-agree с consecutive-failure threshold. С Redis-схемой, кодом и разбором
Аналитик в тумане: как работать с неопределенностью, не притворяясь, что ее нет В работе аналитика данные часто говорят одно, интуиция — другое, а неопределенность сопровождает на каждом шагу. Важно уметь применять ее в свою пользу и не боя
What “false_positive” means
WikipediaA false positive is an error in binary classification in which a test result incorrectly indicates the presence of a condition, while a false negative is the opposite error, where the test result incorrectly indicates the absence of a condition when it is actually present. These are the two kinds of errors in a binary test, in contrast to the two kinds of correct result. They are also known in medicine as a false positive diagnosis, and in statistical classification as a false positive error.
“False positives and false negatives” on Wikipedia (CC BY-SA) →#false_positive across platforms
every network with a public tag surfaceFollow #false_positive straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/false_positive