🚀 آکادمی علوم شناختی دنیای شناخت
دنیایی بینهایت از علم شناخت
www.CognitionWorld.ir
with same id on Linkedin & Instagram
مجموعه رسانههای دنیای شناخت ↓
@cognitiontimes @psychesci @cwkonkoor
Contact & Ads: @CWMediaManager
Created
Between 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 11 August 2026 and assigned it the closest of 31 fixed categories, at 71% 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 the other topics.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Content that also appears on other registered channels
Posts published here appear in near-verbatim form on 1 other registered channel. This entry also forms a group of 2 channels linked by matching posts. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
Matching posts — open both and compare (1 of the pairs behind the counts below)
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. None of the 0 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 32 comparable posts for this entry, running 4 June 2026 to 9 November 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Of the group of 2 channels, the one whose matching posts we hold earliest is @PsycheSci. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_mutual, last confirmed 11 November 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Channels linked by matching posts
This channel is in a group of 2 registered channels linked by matching posts. Links are found by comparing text fingerprints across every channel on the register.
Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
25 measurements spanning 95 days, net +84. 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 8,580–8,702 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 25
Measured (UTC)
Subscribers
Change
10 Nov 2026, 20:21
8,688
+12
7 Nov 2026, 06:09
8,676
+37
4 Nov 2026, 05:30
8,639
+11
1 Nov 2026, 06:10
8,628
+11
29 Oct 2026, 08:36
8,617
+3
23 Oct 2026, 03:56
8,614
-5
19 Oct 2026, 21:55
8,619
+4
17 Oct 2026, 06:31
8,615
+13
14 Oct 2026, 08:55
8,602
-2
10 Oct 2026, 23:21
8,604
+4
4 Oct 2026, 20:36
8,600
-6
25 Sept 2026, 01:36
8,606
+11
13 Sept 2026, 06:57
8,595
-16
9 Sept 2026, 13:00
8,611
-14
4 Sept 2026, 10:01
8,625
+7
31 Aug 2026, 12:55
8,618
-4
28 Aug 2026, 08:04
8,622
-15
24 Aug 2026, 21:38
8,637
+13
21 Aug 2026, 02:44
8,624
+10
17 Aug 2026, 21:37
8,614
first reading
Engagement
41 posts held, back to 9 April 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 43 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
14.3%
avg views ÷ 8,688 subscribers
Avg views / post
1,240
10 posts measured
Reaction rate
1.24%
reactions ÷ views · ER floor
Posts in window
10
of 41 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
Window
Rolling 30 days · latest post in window 9 November 2026
Posts held
41 (9 April 2026 – 9 November 2026)
Views total
12,400
Reactions total
154
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
11 Nov 2026, 12:54 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.
What this channel posts
Photos
615
Videos
204
Links
923
Lifetime counters from Telegram’s own channel header, read 11 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Video runtime
10m 55s
Average length
10m 55s
Measured directly from 1 video with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
623 reactions across 41 posts, in 9 distinct kinds. The most used accounts for 52.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
329
52.8%
👍
82
13.2%
🤣
61
9.79%
🔥
45
7.22%
❤🔥
36
5.78%
😁
23
3.69%
👎
21
3.37%
💔
19
3.05%
👏
7
1.12%
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 41 of the 41 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 623 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 41 most recent posts we hold, published 9 April 2026 to 9 November 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
Telegram’s own ‘edited’ marker: 0 of 10 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
امروزه هوش مصنوعی به یکی از منابع جدید والدین برای دریافت اطلاعات درباره رشد و تربیت کودک تبدیل شده است. از مشکلات خواب و اضطراب جدایی گرفته تا پرخاشگری، تنظیم هیجان و چالشهای رفتاری، موضوعاتی هستند که والدین درباره آنها از ابزارهایی مثل ChatGPT کمک میگیرند. این ابزارها میتوانند اطلاعات علمی را در دسترستر کنند، پیشنهادهای اولیه ارائه دهند و حتی به والدین کمک کنند مسئلهای را که با آن روبهرو هستند بهتر توصیف کنن…
هوش مصنوعی؛ دستیار جدید والدین در تربیت نسل آینده 👼🏻
تصور کنید ساعت یازده شب است. کودک پنجسالهتان هنوز حاضر نیست بخوابد، شما خستهاید و راهکارهایی که تا امروز امتحان کردهاید هم چندان مؤثر نبودهاند. گوشیتان را برمیدارید و از ChatGPT میپرسید: «چطور میتوانم به فرزندم کمک کنم راحتتر بخوابد؟» چند ثانیه بعد، چندین پیشنهاد دریافت میکنید. اما یک سؤال مهم وجود دارد: آیا راهکاری که برای هزاران کودک پیشنهاد میشود، ل…
با سلام و تقدیم احترام خدمت همراهان محترم آکادمی شناخت
طی سه هفته، در یک مجموعه سهقسمتی، سراغ تاریخچهی اکتشافات مهم در علوم اعصاب بینایی میرویم؛ پژوهشهایی که نگاه دانشمندان به نحوه پردازش اطلاعات دیداری در مغز را تغییر دادند.
داستان کشف نقشهای که نورونها از جهان میسازند 🔬
قسمت اول | هارتلاین، ۱۹۴۰
وقتی به محیط اطرافمان نگاه میکنیم، بدون تلاش آگاهانه متوجه میشویم هر شیء کجا قرار دارد. مثلاً بهراحتی تشخی…
📌 از جلبکهای حساس به نور تا کنترل نورونهای مغز
داستان این کشف از مطالعه جلبکهای تکسلولی آغاز شد. پیتر هگمان و گئورگ ناگل، دو پژوهشگر آلمانی که در نوبل امسال با دایسروث شریک هستند، پروتئینهایی حساس به نور به نام «کانالرودوپسین¹» را مطالعه کردند.
این پروتئینها مانند کانالهایی در غشای سلول عمل میکنند که در پاسخ به نور باز میشوند و با عبور یونها، وضعیت الکتریکی سلول را تغییر میدهند.
دایسروث در سال ۲۰۰۴ تصم…
نوبل پزشکی ۲۰۲۶؛ چگونه یک ژن از جلبکها به دانشمندان کمک کرد مغز را بهتر بشناسند؟
کارل دایسروث، دانشمند علوم اعصاب دانشگاه استنفورد، به همراه دو پژوهشگر دیگر، جایزه نوبل فیزیولوژی یا پزشکی ۲۰۲۶ را برای توسعه فناوری اپتوژنتیک دریافت کرد؛ روشی که به دانشمندان اجازه میدهد با استفاده از نور، فعالیت سلولهای عصبی مشخصی را کنترل کنند و به درک تازهای از عملکرد مغز برسند.
📌اپتوژنتیک چیست و چرا اهمیت دارد؟
برای درک اهمیت…
باهوشها دست به رای و دست به خیرتر هستند
افرادی که تواناییهای شناختی بالاتری دارند، بیشتر احتمال دارد در اقداماتی که به نفع جامعه است، مانند کمک به خیریه، رأی دادن در انتخابات و خرید وسایل نقلیه سازگار با محیط زیست، شرکت کنند. این یافتهها نشان میدهد که هوش عمومی نقش مستقیمی در هدایت اقدامات مشارکتی و اجتماعی دارد. این تحقیق در مجله اقتصادی 2026 منتشر شده است.
@cognitiontimes by @cognitionworld
۵ ابزار برای کارهایی که وقت دانشجوها را میبلعند 👩🏼💻
این روزها هوش مصنوعی فقط برای نوشتن متن یا جواب دادن به سؤالها نیست. ابزارهای تخصصی زیادی توسعه پیدا کردهاند که میتوانند بخشهای وقتگیر زندگی دانشجویی، از پیدا کردن مقالات علمی گرفته تا مرور جزوهها و آماده کردن ارائههای کلاسی را سادهتر کنند. در ادامه با پنج ابزار کاربردی آشنا میشویم که بعضی از آنها در سال ۲۰۲۶ قابلیتهای تازهای هم معرفی کردهاند.
✅ جزو…
وقتی چشمها خاموش میشوند، در قشر بینایی مغز چه میگذرد؟ 🧠✨
آیا وقتی فرد بینایی خود را از دست میدهد، قشر بینایی مغز هم غیرفعال میشود؟ یافتههای علوم اعصاب نشان میدهند که لزوماً چنین نیست. قشر بینایی که عمدتاً در ناحیه پسسری مغز قرار دارد، حتی پس از قطع ورودیهای دیداری میتواند در پردازش اطلاعات شنوایی، لمسی و برخی فعالیتهای زبانی مشارکت کند. این پدیده را انعطافپذیری عصبی بینحسی¹ مینامند؛ یعنی مغز در پاسخ به…
اگر قشر بینایی مغز برای «دیدن» ساخته شده، پس چرا در مغز افراد نابینا همچنان فعال است؟ 🤔
آیا ممکن است بخشی از مغز، بدون انجام وظیفه اصلی خود، کارکرد تازهای پیدا کند؟
اگر پاسخ این سوالات برای شما هم جالب هست پست بعدی دنیای شناخت مخصوص شماست!🌱
افزایش درآمد شخصیت آدمها را تغییر میدهد
کسب #حقوق بالاتر میتواند کاری بیش از پر کردن حساب بانکی انجام بدهد؛ عوض شدن تدریجی شخصیت!
بر اساس یک #متاآنالیز بزرگ مقیاس که در مجله روانشناسی بولتن 2026 منتشر شده؛ افزایش درآمد معمولاً همراه است با:
- افزایش اندک در #اطمینان کردن به دیگران
- افزایش کمی در #تابآوری عاطفی
- کاهش در #معاشرت و گرمی بین فردی
یافتهها همچنین نشان میدهد که این رابطه دو طرفه است، به طوری که …
♾️ چرخه در رابطه یعنی چه؟
در درمان هیجانمدار، مخصوصاً در زوجدرمانی، معمولاً مشکل اصلی را فقط «رفتار یک نفر» نمیدانیم؛ بلکه به چرخهای که بین دو نفر شکل گرفته نگاه میکنیم.
زیر رفتارهایی مثل خشم، انتقاد، سکوت یا فاصله گرفتن، معمولاً هیجانهای عمیقتری وجود دارند؛ مثل:
«میترسم برایت مهم نباشم.»
«میترسم ترکم کنی.»
«میترسم هر کاری کنم باز هم کافی نباشم.»
«دلم میخواهد بدانم هنوز کنارم هستی.»
درمان کمک میکند به…
❤12🔥1
Showing the 12 most recent of 41 posts we hold for @CognitionWorld. 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.
Posts recorded as deleted after publishing
We recorded 2 posts on @CognitionWorld as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
26 August 2026
Most recent seen missing
26 August 2026
Median time before seen missing
43 hours
Seen missing in the last 30 days
0
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Named by 6 registered channels — 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.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
ADHD FARSI | روانشناسی @adhdbefarsi · 22,062 Telegram ranks this channel #8 of 82 here — alongside 81 others — read 19 September 2026
Science Magazine @science_magazine · 23,125 Telegram ranks this channel #12 of 95 here — alongside 94 others — read 21 September 2026
کتابخانه روانشناسی تخصصی @Psychological_Tools · 45,485 Telegram ranks this channel #15 of 95 here — alongside 94 others — read 28 August 2026
دیالکتیک علمی @ScientificDialectics · 23,637 Telegram ranks this channel #16 of 95 here — alongside 94 others — read 16 September 2026
دکتر علی صاحبی @drali_sahebi · 21,966 Telegram ranks this channel #19 of 83 here — alongside 82 others — read 24 September 2026
کاپلانخوانی @kaplansadockk · 37,510 Telegram ranks this channel #24 of 97 here — alongside 96 others — read 1 September 2026
ترجمان علوم انسانى @tarjomaanweb · 77,764 Telegram ranks this channel #24 of 96 here — alongside 95 others — read 29 August 2026
آکادمی زبان روانشناسی @PsyEngAcademy · 24,093 Telegram ranks this channel #26 of 95 here — alongside 94 others — read 24 September 2026
دکتر آذرخش مُکری @drazarakhsh_makri · 33,454 Telegram ranks this channel #26 of 86 here — alongside 85 others — read 6 September 2026
درمان شناختی رفتاری CBT @CBTRAVAN1 · 23,159 Telegram ranks this channel #30 of 88 here — alongside 87 others — read 20 September 2026
یافتههای نوین روانشناختی @Hrman11 · 24,203 Telegram ranks this channel #30 of 90 here — alongside 89 others — read 18 September 2026
علوم اجتماعی،مسائل روز @social_science · 24,577 Telegram ranks this channel #30 of 90 here — alongside 89 others — read 17 September 2026
بنیاد مرهم 🫀 Marham Foundation @Marham_Foundation · 18,368 Telegram ranks this channel #31 of 90 here — alongside 89 others — read 4 October 2026
دانش، آگاهی @daneshagahi · 28,685 Telegram ranks this channel #31 of 95 here — alongside 94 others — read 10 September 2026
دکتر محمدرضا سرگلزایی drsargolzaei @drsargolzaei · 35,620 Telegram ranks this channel #32 of 95 here — alongside 94 others — read 2 September 2026
🕊 فرازتد⚡️(روشنگری) @FarazTed · 21,173 Telegram ranks this channel #33 of 92 here — alongside 91 others — read 26 September 2026
Science Documentaries مستندهای علمی @Documentary20 · 24,160 Telegram ranks this channel #33 of 91 here — alongside 90 others — read 19 September 2026
کانال آموزشی دکتر مینا صافی @drminasafi59 · 26,665 Telegram ranks this channel #33 of 90 here — alongside 89 others — read 11 September 2026
کتابخانه بین المللی @LibraryinternationaL · 20,364 Telegram ranks this channel #34 of 89 here — alongside 88 others — read 26 September 2026
مرکز مشاوره دانشگاه تهران @UTcounseling · 24,660 Telegram ranks this channel #37 of 99 here — alongside 98 others — read 15 September 2026
Spirit_and_life_ | روانشناسی تحلیلی یونگ @Spirit_and_life · 40,558 Telegram ranks this channel #51 of 94 here — alongside 93 others — read 1 September 2026
جزوات کنکوری روانشناسی @jozveravan1 · 23,707 Telegram ranks this channel #55 of 87 here — alongside 86 others — read 20 September 2026
پُرتال کتاب و جزوات روانشناسی @PsyPortalBook · 35,442 Telegram ranks this channel #55 of 97 here — alongside 96 others — read 3 September 2026
انبارستان🎧 @anbar100 · 29,569 Telegram ranks this channel #57 of 89 here — alongside 88 others — read 9 September 2026
This channel appears in 36 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 10 November 2026 — this
entry's latest reading, not the date you are reading this.
“آکادمی دنیای شناخت” (@CognitionWorld), 8,688 subscribers as measured 10 November 2026. Telegram Register, tgregister.com/channel/CognitionWorld.
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.