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Channel

3D Smile

@smile_aligners_lab

On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry

1,083subscribers

-6 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1002272567379
TypeChannel
Username@smile_aligners_lab
CreatedBetween 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live30 August 2026
Measurements held8
Confirmed unchanged1 time, most recently 30 August 2026
On Telegramt.me/smile_aligners_lab

Growth

1,0831,0891,0867 August 2026 — 1,089 subscribers7 August 2026 — 1,089 subscribers11 August 2026 — 1,087 subscribers17 August 2026 — 1,088 subscribers21 August 2026 — 1,086 subscribers24 August 2026 — 1,085 subscribers27 August 2026 — 1,084 subscribers30 August 2026 — 1,083 subscribers7 August 202630 August 2026
8 measurements spanning 23 days, net -6. 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 1,082–1,090 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
30 Aug 2026, 10:451,083-1
27 Aug 2026, 15:341,084-1
24 Aug 2026, 23:331,085-1
21 Aug 2026, 02:021,086-2
17 Aug 2026, 20:361,088+1
11 Aug 2026, 06:261,087-2
7 Aug 2026, 20:551,089no change
7 Aug 2026, 06:311,089first reading

Engagement

9 posts held, back to 21 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
13.3%
avg views ÷ 1,083 subscribers
Avg views / post
144
3 posts measured
Reaction rate
9.98%
reactions ÷ views · ER floor
Posts in window
3
of 9 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.

What these figures were computed from
WindowRolling 30 days · latest post in window 4 August 2026
Posts held9 (21 July 20264 August 2026)
Views total431
Reactions total43
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 06:31 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

Reaction mix

107 reactions across 9 posts, in 9 distinct kinds. The most used accounts for 41.1% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
4441.1%
🔥2220.6%
👏1816.8%
❤‍🔥1110.3%
🥰43.74%
🤗32.80%
🆒21.87%
🤩21.87%
🏆10.935%

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 9 of the 9 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 107reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 9 most recent posts we hold, published 21 July 2026 to 4 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Recent posts

4 Aug 2026, 15:26 UTC128 views11 reactionsread 7 August 2026
Photo

Челябинск, спасибо! 💚 Команда 3D Smile провела в Челябинске сразу два насыщенных образовательных дня. Первый день вместе с клиническим директором 3D Smile Яниной Акопян посвятили теме, которая сегодня определяет успех лечения не меньше, чем точное клиническое планирование, — доверию между врачом и пациентом. Обсудили, как современные пациенты принимают решение о начале лечения и что помогает сохранять их мотивацию

4❤‍🔥2👏2🔥1🤩1🆒1

4 Aug 2026, 15:26 UTC138 views12 reactionsread 7 August 2026
Photo

Во второй день мы полностью погрузились в клиническую практику. Для проведения мероприятия к нам присоединились наши друзья и партнеры из Челябинска: Лазарева Ольга Вячеславовна — врач-ортодонт, к.м.н., доцент кафедры ортопедической стоматологии и ортодонтии ЮУГМУ, руководитель клиники интеллектуальной ортодонтии «ОртоБьюти» — посвятила свое выступление диагностике как главному этапу планирования лечения и поделил

5👏3❤‍🔥2🔥1🥰1

4 Aug 2026, 08:27 UTC165 views20 reactionsread 7 August 2026
Photo

Технорелиз 3D Smile: новый Личный кабинет врача Дорогие коллеги! Этот год для 3D Smile проходит под знаком масштабных изменений. Мы представили новый визуальный голос бренда, обновили пациентскую упаковку, фирменный стиль и продолжаем развивать каждый этап взаимодействия с продуктом. Сегодня мы рады представить новый Личный кабинет врача — современное цифровое пространство для вашей ежедневной работы. За этим рез

🔥7👏5🥰32🏆1🤩1🆒1

28 Jul 2026, 10:33 UTC380 views21 reactionsread 7 August 2026
Photo

Немного добрых новостей в вашу ленту! В прошедшие выходные компания 3D Smile стала участником проекта со смыслом — «Сажай, Питер!», посвящённого озеленению Санкт-Петербурга. Для нас это возможность заботиться не только о красоте улыбок, но и об экологии города, где живут и работают наши врачи, пациенты и их семьи. Особую благодарность хотим выразить Быковой Евгении Владимировне — врачу-ортодонту и основательнице кл

13👏4🤗3❤‍🔥1

22 Jul 2026, 10:30 UTC308 views5 reactionsread 7 August 2026

Разбираем клинические случаи из практики врачей-участников

4❤‍🔥1

22 Jul 2026, 10:30 UTC299 views7 reactionsread 7 August 2026
Video message

Video message, posted without a caption

❤‍🔥32🔥2

22 Jul 2026, 10:13 UTC280 views8 reactionsread 7 August 2026
Video

Вы часто отмечаете, как вам нравятся места, которые мы выбираем для наших образовательных встреч 🤍🥹 Мы действительно тщательно подходим к выбору каждой локации, чтобы мероприятия проходили в комфортной атмосфере и оставляли приятные впечатления не только от программы, но и от самого пространства. Актуальное расписание всех предстоящих событий всегда доступно в вашем личном кабинете по ссылке 🔗

4🔥3❤‍🔥1

22 Jul 2026, 08:45 UTC241 views7 reactionsread 7 August 2026
Photo

Сегодня для московских врачей проходит встреча с клиническим директором 3D Smile Яниной Акопян. В программе — разбор клинических случаев, обсуждение современных подходов к диагностике и выбору тактики лечения, профессиональный диалог с коллегами и ответы на актуальные вопросы врачей.

🔥42❤‍🔥1

21 Jul 2026, 11:26 UTC254 views16 reactionsread 7 August 2026
Photo

Элайнеры как инструмент выбора для лечения пародонтологических пациентов Сегодня хотим затронуть очень важную для каждого ортодонта тему — лечение пародонтологических пациентов. Такие пациенты требуют особого подхода: применения специальных протоколов и мягких сил, чтобы не усугубить уже имеющуюся ситуацию. Прекрасным инструментом для достижения целей по коррекции прикуса в подобных случаях выступают элайнеры 3D Smi

8👏4🔥4

Showing the 9 most recent of 9 posts we hold for @smile_aligners_lab. 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.

Citation-graph rank

Citation-graph rank — 350,224 of 1,627,445entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

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 30 August 2026 — this entry's latest reading, not the date you are reading this.

“3D Smile” (@smile_aligners_lab), 1,083 subscribers as measured 30 August 2026. Telegram Register, tgregister.com/channel/smile_aligners_lab.

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.