Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 19 September 2026 and assigned it the closest of 31 fixed categories, at 67% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Growth
7 measurements spanning 42 days, net -69. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 853–942 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
19 Sept 2026, 14:17
863
-9
11 Sept 2026, 06:56
872
-9
1 Sept 2026, 15:13
881
-12
25 Aug 2026, 00:06
893
-10
17 Aug 2026, 10:57
903
-26
9 Aug 2026, 10:53
929
-3
8 Aug 2026, 11:34
932
first reading
Engagement
8 posts held, back to 15 July 2024 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 8 posts for this entry, the most recent from 14 October 2024. An engagement rate over an empty window would be a number about nothing.
Reaction mix
782 reactions across 6 posts, in 8 distinct kinds. The most used accounts for 35.7% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
279
35.7%
❤
253
32.4%
🎉
135
17.3%
👍
108
13.8%
🤝
2
0.256%
🤩
2
0.256%
🥰
2
0.256%
👏
1
0.128%
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 6 of the 8 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 782 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 8 most recent posts we hold, published 15 July 2024 to 14 October 2024, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
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📰 Прочитывая последние новости про Байкал, аж становиться плохо.
Главная беда это Ольхон..
🪄 Чудный 🏝️ чудный остов по среди Байкала на который хотят попасть несколько тысяч туристов. И это становиться глобальной проблемой экологии и туризма.
🧑🏭 Строительство экологически устойчивого завода легко вписывается в цели Nerpa по обеспечению чистоты и сохранности Байкала. Путем контроля выбросов …
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🚶♂️ Начните свой путь к Байкалу уже сегодня! Мы уверены, что с вашей под…
🌟 ВНИМАНИЕ ВСЕМ!
🏭 Уже скоро откроется новый, уникальный завод от Nerpa!
Он будет столь же удивителен и важен, как сам Байкал! 🌊
🏭 Что же это за завод?
🛠️ Вот что он будет делать:
Завод №1:
👉 Добыча ⛏️ радиационного мусора Tap-to-Earn ( добываем ресурсы gNRB)
👉 Переработка ♻️ радиационного мусора в чистый $NRB
👉 Использование gNRB в заводе в качестве топлива для производства энергии ☢️
🤳 Более того, ты…
🌊 Привет, друзья!
Меня зовут NERPA (NRB).
Я - существо, которое любит плавать в кристально чистой воде Байкала. Это мой удивительный дом 🐚, и я всегда стараюсь очищать его берега и воду от мусора 🗑️, особенно от такого ужасного явления, как пластиковые отходы.♻️
📢 Я рассказала своим друзьям из Baikal Wood о своей идее создания завода для переработки ♻️ пластика, и они сразу согласились помочь мне.. 🤗🤗🥳
Я жду с не…
🌲Baikal Wood: Экологический Центр и Инновационная Платформа для Международного Экотуризма на Байкале.
🫶 Мы рады представить вам Baikal Wood - уникальный экологический центр, который станет пионером в развитии международного экотуризма на Байкале.
Наш центр приглашает гостей и туристов с целью обеспечить им комфортную акклиматизацию и дальнейшее продвижение к лучшим местам для отдыха на Байкале.
🚮 Экологическая у…
Showing the 8 most recent of 8 posts we hold for @baikal_wood_rus. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Mentions
Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 19 September 2026 — this
entry's latest reading, not the date you are reading this.
“Baikal Wood” (@baikal_wood_rus), 863 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/baikal_wood_rus.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.