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하나증권 리서치

@HanaResearch

On this record: Topic · Observations · Also posting the same content · Growth · Engagement · Posts · Posts edited after publishing · Citations · Cite this entry

24,968subscribers

+511 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001147595657
TypeChannel
Username@HanaResearch
Created7 June 2017measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live19 September 2026
Measurements held33
Confirmed unchanged1 time, most recently 19 September 2026
On Telegramt.me/HanaResearch

Topic

Crypto & trading — 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 10 August 2026 and assigned it the closest of 31 fixed categories, at 73% 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.

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 word for word on 2 other registered channels. They sit inside a group of 5 channels that share the same post bodies with each other. 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 (6 of the pairs behind the counts below)
Posted firstThenOverlapGap
@HanaResearch/20131 · this entry5 Aug 2026, 06:39 UTC@hanaglobalbottomup/88045 Aug 2026, 06:39 UTC1.00under a minute
@hanaglobalbottomup/88096 Aug 2026, 00:37 UTC@HanaResearch/20146 · this entry6 Aug 2026, 00:37 UTC1.00under a minute
@HanaResearch/20152 · this entry6 Aug 2026, 07:18 UTC@hanaglobalbottomup/88136 Aug 2026, 07:18 UTC1.00under a minute
@HanaResearch/20158 · this entry6 Aug 2026, 23:24 UTC@hanaglobalbottomup/88176 Aug 2026, 23:25 UTC1.00under a minute
@HanaResearch/20131 · this entry5 Aug 2026, 06:39 UTC@globaletfi/209775 Aug 2026, 07:49 UTC1.0070 minutes
@HanaResearch/20152 · this entry6 Aug 2026, 07:18 UTC@globaletfi/209996 Aug 2026, 15:01 UTC1.007.7 hours
Every channel this entry shares post bodies with
ChannelMatching postsText overlapTypical gapPublished first
@hanaglobalbottomup7 (7/7 hand-verifiable sample passed)1.00under a minute@hanaglobalbottomup (52)
@globaletfi5 (5/5 hand-verifiable sample passed)1.0059 minutesthis entry (50)

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. 1 of the 1 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.

“Published first” means first in this corpus. We hold 31 comparable posts for this entry, running 5 August 2026 to 7 August 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).

Across the whole group of 5, the earliest publisher we hold is @hanaglobalbottomup. That is a statement about our reading window, not a claim of authorship.

Recorded under the keys clone_mutual · clone_source, last confirmed 7 August 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.

Also posting the same content

This channel’s posts match, word for word or near enough, posts on 4 other registered channels, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.

Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word 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.

Growth

24,45624,96824,7126 August 2026 — 24,457 subscribers6 August 2026 — 24,457 subscribers6 August 2026 — 24,456 subscribers7 August 2026 — 24,472 subscribers8 August 2026 — 24,480 subscribers10 August 2026 — 24,493 subscribers11 August 2026 — 24,488 subscribers12 August 2026 — 24,486 subscribers13 August 2026 — 24,492 subscribers14 August 2026 — 24,494 subscribers17 August 2026 — 24,499 subscribers18 August 2026 — 24,507 subscribers19 August 2026 — 24,513 subscribers20 August 2026 — 24,523 subscribers22 August 2026 — 24,537 subscribers23 August 2026 — 24,612 subscribers25 August 2026 — 24,650 subscribers26 August 2026 — 24,666 subscribers26 August 2026 — 24,667 subscribers28 August 2026 — 24,672 subscribers29 August 2026 — 24,668 subscribers30 August 2026 — 24,684 subscribers31 August 2026 — 24,697 subscribers1 September 2026 — 24,706 subscribers2 September 2026 — 24,701 subscribers3 September 2026 — 24,734 subscribers5 September 2026 — 24,750 subscribers8 September 2026 — 24,761 subscribers11 September 2026 — 24,767 subscribers13 September 2026 — 24,821 subscribers14 September 2026 — 24,851 subscribers16 September 2026 — 24,929 subscribers19 September 2026 — 24,968 subscribers6 August 202619 September 2026
33 measurements spanning 44 days, net +511. 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 24,379–25,045 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 33
Measured (UTC)SubscribersChange
19 Sept 2026, 09:5424,968+39
16 Sept 2026, 21:3924,929+78
14 Sept 2026, 22:4024,851+30
13 Sept 2026, 09:0024,821+54
11 Sept 2026, 11:2124,767+6
8 Sept 2026, 19:2124,761+11
5 Sept 2026, 09:5624,750+16
3 Sept 2026, 10:1324,734+33
2 Sept 2026, 02:5724,701-5
1 Sept 2026, 03:1524,706+9
31 Aug 2026, 04:5424,697+13
30 Aug 2026, 02:2424,684+16
29 Aug 2026, 02:4824,668-4
28 Aug 2026, 01:0824,672+5
26 Aug 2026, 23:5424,667+1
26 Aug 2026, 01:5324,666+16
25 Aug 2026, 02:1424,650+38
23 Aug 2026, 13:4624,612+75
22 Aug 2026, 01:1724,537+14
20 Aug 2026, 22:4224,523first reading

Engagement

219 posts held, back to 5 August 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 59 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
6.42%
avg views ÷ 24,968 subscribers
Avg views / post
1,600
76 posts measured
Reaction rate
this channel exposes no reaction counts
Posts in window
76
of 219 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 3 September 2026
Posts held219 (5 August 20263 September 2026)
Views total121,857
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken3 Sept 2026, 10:39 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.

Recent posts

3 Sept 2026, 08:15 UTC544 viewsread 3 September 2026
Forwarded from @hana_us_stock

◈하나증권 해외주식분석◈ 선진국 기업분석 강재구(T.02-3771-3386) *텔레그램 채널: https://t.me/hana_us_stock ★ H.P. Enterprise Co. (HPE.US): 수요는 충분, 공급망 확보가 관건 ▶ 자료: https://buly.kr/DPWcaXF ▶ 4분기 주문의 매출 전환 가속 확인 필요 - 휴렛패커드 엔터프라이즈(HPE)의 실적에서 시장참여자들이 실망한 점은 강한 수요를 매출로 빠르게 전환시키지 못한 점이다. 수요가 강하다는 점에서 중장기 긍정적인 관점을 유지하지만, 단기적으론 델 테크놀러지스와 비교될 여지가 있다. 델은 AI 서버 매출 증가와 함께 이익률 개선까지 보여줬으나, HPE는 공급 제약으로 주문의 매출 전환이 늦고 AI 시스템 비중 확대에 따른 수익성 정상화를 예고했다는 점에서 단

3 Sept 2026, 06:14 UTC808 viewsread 3 September 2026
Forwarded from @hanaglobalbottomup

◈하나증권 해외주식분석◈ 미국/선진국 기업분석 김시현(T.02-3771-7513) *텔레그램 채널: https://t.me/hanaglobalbottomup ★ GE 버노바(GEV.US): 스페이스X의 가스터빈 진출 코멘트 ▶ 자료: https://buly.kr/5UKWPzM ■ 스페이스X의 터빈 블레이드와 베인 진출 가능성 보도 - 8월 말 The Information은 스페이스X의 가스터빈 블레이드와 베인 파운드리를 구축 중이라고 보도 - 같은 날 오후 머스크는 X에 “스페이스X와 테슬라는 각각 연간 100GW의 태양광 캐파를 구축 중이나 천연가스는 태양광을 뒷받침하는 데 여전히 필요하며 스페이스X는 자체 주조를 통해 가스터빈 가동 시기를 최대 18개월 앞당길 수 있다” 며 보도를 사실상 인정 - GE버노바 등 기존 가스터빈 제조사

3 Sept 2026, 00:13 UTC≈1,190 viewsread 3 September 2026
Forwarded from @hanaallocation

[자산배분의 창(窓)] 가계 연체율은 높은데, 미국 소비는 왜 견조할까 하나 자산배분/해외크레딧 이영주(T.3771-7788) ▶ 자료: https://bit.ly/4h68ZgJ ▶ 채널: https://t.me/hanaallocation > 높아진 금융부담, 식지 않는 소비 열기 - 26.2Q 미국 실질 GDP 성장률은 전분기 대비 연율 2.1%에서 1.5%로 둔화한 반면, 개인소비 증가율은 0.5%에서 3.4%로 가속. 신용카드와 자동차대출 연체율은 금융위기 수준, 개인 저축률은 약 4년래 저점. HELOC 잔액도 17개분기 연속 증가해 4,590억 달러. 즉, 가계 재무 부담에도 소비는 예상보다 강한 흐름 - 괴리의 기본적 요인은 안정된 고용. 일자리가 유지되면 가계 소득 유입은 계속. 높은 주택가격과 주가 상승은 가계 자산가치를

2 Sept 2026, 23:38 UTC≈1,690 viewsread 3 September 2026
Photo

Hana Global Guru Eye(26.09.03) [9월 3일 Hana Global Guru Eye] ▶ 하나증권 리서치센터 글로벌투자분석실 : https://buly.kr/2Jqsetc ▶ 오늘의 리포트 링크 1. [유틸리티/2차전지 In-depth] Electro-state, 대전환의 시작 : https://buly.kr/DaRNG8D 2. [월간 하나채권] [9월] 진짜 긴축은 이제 시작 : https://buly.kr/1GMKlWs

2 Sept 2026, 09:35 UTC≈1,450 viewsread 3 September 2026

미국 자동차 판매 동향(2026년 8월): HEV 위주의 성장. 하반기 모델 추가 투입으로 관련 모멘텀 강화 [하나증권 자동차 Analyst 송선재] Key Insight: 미국 내 점유율 상승은 긍정적이나, 미국 의존도가 커지고 있다는 부담도 증가 ▶ 산업 - 미국 자동차 소매판매는 8월 -5% (YoY). 8월 누적으로도 -0% (YoY) 기록 - 파워 트레인별로는 내연기관차/전기차/하이브리드차가 각각 -5%/-26%/+19% (YoY) 기록 - 전기차 판매는 전년 9월 전기차 세액공제 종료 후 10개월 평균 -27% (YoY)로 부진. 기저 효과가 발생하는 11월 전까지는 부진할 전망 - 하이브리드차는 전체 시장대비 상회한 성장을 보이며, 침투율이 15%대 중반까지 상승. 전년 동기대비 3%p 상승한 것 - 현대차/기아의 미국 판매

2 Sept 2026, 09:35 UTC≈1,030 viewsread 3 September 2026

글로벌 친환경차/2차전지 Monthly (2026년 7월): EV +8%. 미국/중국 부진. 유럽 나홀로 강세의 심화 [하나증권 Analyst 자동차 송선재/2차전지 김현수] ▶ 전기차(BEV+PHEV) 판매 (1) 글로벌: 176.4만대(+8% (YoY), 비중 21.9%) (2) 미국: 9.3만대(-39% (YoY), 비중 6.8%) (3) 중국: 94.8만대(-5% (YoY), 비중 64.3%) (4) 유럽: 43.5만대(+35% (YoY), 비중 N/A) (5) 한국: 2.1만대(+45% (YoY), 비중 14.8%) ▶ 하이브리드차 판매 (1) 글로벌: 100.2만대(+12%) (2) 미국 23.4만대(+29%) (3) 유럽 35.6만대(+9%) (4) 일본 18.1만대(+4%) (5) 한국 3.4만대(flat) ▶ 현대차/기

2 Sept 2026, 08:49 UTC≈1,150 viewsread 3 September 2026
Forwarded from @hana_us_stock

◈하나증권 해외주식분석◈ 선진국 기업분석 강재구(T.02-3771-3386) *텔레그램 채널: https://t.me/hana_us_stock ★ Dell Technologies (DELL.US): FY 2Q27: AI 수요와 이익 개선이 맞물리는 선순환 ▶ 자료: https://buly.kr/4bkjBn1 ▶ 매출, 이익 동반 서프라이즈 - 델 테크놀러지스(이하 델)에 대한 긍정적인 관점을 유지한다. 시장 참여자들은 델 제품의 양호한 수요에 대해선 긍정적으로 평가하면서도, 메모리와 GPU 등 서버 부품 가격 상승에 따른 수익성 훼손을 걱정했었다. 우려와 달리 외형 성장과 함께 수익성도 개선됐으며, 호실적을 기반으로 연간 실적 가이던스도 상향했다. 핵심 사업부인 인프라 사업부의 이익 개선이 전사 수익성 향상을 주도했다. - 강력한

2 Sept 2026, 00:21 UTC≈1,620 viewsread 3 September 2026
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Hana Global Guru Eye(26.09.02) [9월 2일 Hana Global Guru Eye] ▶ 하나증권 리서치센터 글로벌투자분석실 : https://buly.kr/CWwpCco ▶ 오늘의 리포트 링크 1. [Hana 미국주식 Monthly] 9월의 계절성 주의 필요하지만, 미국주식 선호 유지 : https://buly.kr/5JPkyuq 2. [프론트라인] VLCC 시장: 톤마일 증가와 환적 증가 : https://buly.kr/6ijopRy

1 Sept 2026, 22:46 UTC≈1,580 viewsread 3 September 2026
Forwarded from @hanabond

[월간 하나채권] [9월] 진짜 긴축은 이제 시작 ▶ 인상 시점이 아닌 최종 금리에 주목. 성장세와 물가압력, 그리고 미-이 확전은 상방 요인 ▶ 미국: 유동성 팽창과 기저 인플레이션 압력 지속. 연준의 인상은 시간 문제 ▶ 한국: 성장이 모든 것을 설명. 인상 속도 조절과 국채 발행 감소에도 금리는 상승 *보고서: https://bitly.cx/r28y 채권전략 박준우 (T.3771-7262) (컴플라이언스 승인을 득함)

1 Sept 2026, 21:51 UTC≈1,920 viewsread 3 September 2026

[하나증권 건설 김승준] 9/2 건설(Overweight) - 2027년 예산안 분석 ▶리포트: https://buly.kr/2Jqs4Pv 2027년 예산안과 26~30년 국가재정운용계획이 발표됐습니다. 2027년 예산 지출은 820.9조원(+9.0%yoy)이며, 국가채무는 1,520조원(+7.6%yoy)로 계획했습니다. 건설 관련해서는 국토부 예산이 69조원(+9.9%yoy)이며, 작년대비 6.2조원 증액됐는데 주택이 8.8조원 증액됐습니다. 2027년에 공적주택 21.8만호(공공임대 17.2만호, 공공분양 3.4만호, 공공지원민간임대 1.2만호)를 30조원 투입하여 공급합니다. 그리고 역세권/중형평형의 보편형 임대주택 3.6만호(건설형임대 2.6만호/4.8조원, 매입형임대 0.5만호/0.5조원, 전세임대 0.5만호/0.9조원)도 신설

1 Sept 2026, 12:31 UTC≈1,730 viewsread 3 September 2026

* 하나증권 미래산업팀 * 스몰캡/로봇/AI (Analyst 한유건, 권태우, 박찬솔) ★ 반도체 소재·부품·장비(Overweight): 증설의 시대, 후공정의 수혜도 함께 온다 ★ 원문링크: https://buly.kr/7x97fKy 1. HBM에 범용 증설이 더해진다, 총량이 늘어나는 국면 - HBM 투자가 이어지는 가운데 범용 DRAM·NAND 증설이 더해지며 메모리 웨이퍼 투입과 생산량이 함께 늘어나는 국면에 진입 - 직전 사이클에서는 기존 캐파의 HBM·선단 노드 전환에 집중되면서 웨이퍼 총량 증가가 제한됨 - 반면, 평택 P4와 M15X의 램프가 진행되는 가운데 용인 Y1의 장비 발주와 평택 P5의 장비 공급사 선정 등 후속 일정도 구체화되고 있음 - 산업 자료 기준 DRAM 웨이퍼 투입은 2027년까지 2025년 대비 15%

1 Sept 2026, 10:52 UTC≈1,390 viewsread 3 September 2026
Forwarded from @yskoh1

증권(Overweight): 낮아진 거래대금과 높아진 이익 체력 자료: https://bit.ly/4cptLWa □ 8월 국내증시 일평균 거래대금 49.6조원(MoM -25.2%) 8월 국내증시 일평균 거래대금은 49.6조원(KRX 31.8조원, NXT 17.7조원)으로 전월대비 25% 감소. 3분기 누적 국내증시 일평균 거래대금은 58.3조원(KRX 37.7조원, NXT 20.6조원)으로 2분기 90조원을 크게 하회 8월 ETF 일평균 거래대금은 17.6조원으로 전월대비 47% 감소. 3분기 누적 ETF 일평균 거래대금은 25.6조원으로 2분기대비 9% 감소. 특히 한때 ETF 거래대금의 40%를 차지했던 단일종목 레버리지 ETF 거래비중이 5% 수준까지 급락하면서 증시 변동성이 축소되고, 이에 따라 전체 거래대금 역시 감소하는 흐름이

Showing the 12 most recent of 219 posts we hold for @HanaResearch. 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 edited after publishing

@HanaResearch edited 2 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.

An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.

First edit seen
11 August 2026
Most recent edit
14 August 2026

Forward network

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 3 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.

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.

“하나증권 리서치” (@HanaResearch), 24,968 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/HanaResearch.

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.