Orwell2024🏒 Profile picture
Jun 7, 2021 15 tweets 7 min read Read on X
1/ A great summary! After having peer reviewed many papers in the past, I can't leave this uncommented. There is just too much truth in it. But also many things missing. @markdhumphries

elemental.medium.com/the-absurdity-…
2/ "only one of Einstein’s 300 or so published papers was ever peer-reviewed, which so disgusted him that he never submitted a paper to that journal again."

He was not alone. Nature rejected Kary Mullis PCR paper (Nobel Price awared).

And what about drasticresearch.org/our-works/
3/ Peer Review is nothing more than "please have a look". It's a basic check, not a quality endorsment. Most papers I received were Chinese low quality papers pushing into high-end journals like Phys. Rev. B or Phys. Rev. Letters. I rejected (or redirected elswhere) most of them.
4/ It was clear that pushing low quality into high-end journals was about reputation and money. It's a quantitative money game, driven by the sick funding process in science. The more I rejected (or redirected elsewhere), the more I received from Phys. Rev. I noticed empirically
5/ Other reviewers may not be critical, so the flooding tactics to the high-end obviously works by being lucky (catching e.g. a lazy "ok" reviewer). For my own papers, I considered such high-end flooding tactic as unmoral to engage in. Nice small conferences are fine too for me.
6/ "much peer review is aggressive, rude, lazy, or just plain bad.".

You nailed it!

We don't get paid for this, so what do you expect? Quality? Most papers are bad, so it's really not fun nor a popular task to proof read. 99.99..% of the papers are not breaking discoveries.
7/ When a paper drops in for review, what is more likely? A) You drop your work or B) you pass it on to the PhD student? At some point, when Phys. Rev. sent too much, I started to reduce, reject or pass on. Checking the "not my field" box was the fastest way out for boring papers
8/ Peer Review is NOT a quality stamp nor a "certification" like mainstream COVID manic media claims.

"Does it stop a plainly wrong or plainly nonsense paper from being published? No"

Examples? @ConceptualJames @peterboghossian demonstrated:

9/ The article forgot to mention another issue: Rivality between competing groups. Dirty games may be played on the high end front. Rejection in order to publish ahead. At least that's what rumors tell for high impact publications on Moore's law research. Not seen it myself.
10/ Academic integrity and courage at the level of @ConceptualJames @BretWeinstein @peterboghossian @SwipeWright is exceptionally rare. They deserve a big thank you in this sinister "post factual" propaganda times of political science.
12/ The weak point seems to be at the editorial level. Once you get a political agenda pushing admin on such post, it's game over. In science and media. Nice example is @ggreenwald (also a shining star) who resigned from the outlet he co-founded.
theguardian.com/media/2020/oct…
13/ Team #DRASTIC has shown us the pathway for the future. It's time to scarp and wrap-up the dead dinosaurs, both in media and science journals.

Ideally we should have a block chain version of an uncensorable version of Twitter for science with a built in pre-print database.
14/ Closing words: "Satoshi Nakamoto" un-reviewed #bitcoin paper provided a solution to a long unsolvable mathematical problem: "The #Byzantine Generals’ Problem". A major mathematical discovery with disruptive impact on society.
bitcoin.org/bitcoin.pdf
link.medium.com/8tpn7lYHWgb

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with Orwell2024🏒

Orwell2024🏒 Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @orwell2022

Jun 12
1/ Back to Japan temperature trends.

We now add a smaller town: Suttsu. Still not truly rural nor stable site, but better.

We now show:
🟥 Kyoto
⬛️ Tokyo
🟦 Suttsu

Can you see it?

They then aggregate urban-biased data (rot) like this and call it “global temperature.” Image
2/ Here it is: Suttsu.

Not a high-quality reference site like
Valentia Observatory (Ireland) or h-USCRN sites.

But: Lower urban bias than cities like Kyoto or Tokyo. It starts to show the well known flatliner we see at stable sites. Image
Image
3/ To see it better, here’s 4 months side by side:

🟥 Kyoto
⬛️ Tokyo
🟦 Suttsu

This is man-made. The T trend is just unrelated to climate. It measures the site and environment change. Suttsu as expected least impacted. But it still is. Image
Read 11 tweets
May 27
The red areas are fully man-made—built or cultivated.
You cannot measure climate anywhere near them.
And MODIS still misses a lot.
In reality, it’s worse.

When we inspected what @BerkeleyEA calls “rural”?
Almost all those stations are worthless Image
Imagine a field looks like it does on the left…alive.
And later, like the right. Dead and brown.
Still think you'll measure the same 2m temperature?
Or might that just—possibly—have a major impact as the surroundings changed? GPT estimates 3C. It's not wrong. Image
Image
Image
We now combine MODIS 🟥 and P2023A 🟪 (10m resolution).

Look: MODIS misses entire urban zones— Ireland. Or Liverpool.

And yet @hausfath and @BerkeleyEarth built their “rural” claims on MODIS junk.
Shameful deception.
The paper needs a retraction.
Image
Read 6 tweets
May 23
Maybe some still don’t grasp the novelty here. This shows what the “climate consensus” is built on: MODIS — a coarse, fully outdated DB.

Now compare that to P2023A.

So—@BerkeleyEarth @hausfath—still think your pick is better? Let me know. And explain why. Image
Thanks to this trick, they labeled urban sites as “rural”—then obviously saw no difference.
That paper must be retracted.
Back then: resolution limits.
Today? Ignoring P2023A is agenda.
Anyone can open Google Earth and see houses where MODIS finds none.

Image
In a nutshell: using decades-old MODIS (500m, binary) to argue “nothing’s there” versus P2023A 10m high res color is like claiming your iPhone 1 low-light photo proves the room was empty—
while the iPhone 16 Pro with AI sees everything.
Only dishonest clowns run that defense.
Read 9 tweets
May 9
1/ April resists warming.
Remember: warming causes cooling.
If you’re freezing, you're actually warming.
Colder weather confirms it’s warmer.
We must prevent cooling to stop warming.
Yes, it still was the warmest April in SW models.
Now pay your CO2 tax please and eat vegan. Image
2/ We check ourselves. The ClimDiv curve is even cooling 1.37C compared with the stable USCRN sites. Image
3/ Expand the range to 115 years.
Stable USCRN sites show nothing.
ClimDiv now shows warming—entirely from adjustments.
Wrong ones: cooling rural, not towns.
Signal upside down.
That's not science—it’s appalling. Image
Read 6 tweets
May 5
1/ This proxy is the most dishonest narrative in the entire climate agenda.
Anyone pushing it isn’t doing science — they’re signaling allegiance.
If you still treat them seriously, that’s on you.
They’re not analysts. They’re ideological fools. #ClimateScam Image
Image
2/ Last week of April 2025. Rural Nagano. ~700m elevation. Full bloom.
I challenge the town-proxy scammers to show us blooming in late May or June a hundred years ago.
Go ahead— make fools out of yourself by failing.
👉The consensus now = defund climate activists (“academics”). Image
Image
Image
Image
3/ …been cultivated in Japan since the Edo and Meiji periods. Bloom timing is widely celebrated, recorded, and scheduled for festivals.. There are no records of cherry festivals here occurring in late May or June. That would have been seen as “weirdly late,” even then… Image
Image
Image
Image
Read 6 tweets
Apr 12
1/ I was told non US GHCN “raw” is adjusted already.

-----TRUE-----

Now I see it. Gosh.

Composite. 2x adjusted. NOAA doesn’t even know where non-US stations are—or what they’re measuring. Their own US data (USCRN) is light-years better. But for “global”? It’s clown-tier level. Image
2/ And here it is—the DOUBLE-adjusted COMPOSITE.
Not raw. I doubted @connolly_s at first—like someone denying their 2nd-hand car is stolen, crash-salvaged, and repainted twice. Turns out he was right.
NOAA’s “global” QCU (non-US): not raw.
Image
Image
3/ Credit where due.
Normally I block on first bad-faith signal.
But intuition said: bait him back.
Let’s see what he hands over.
And he did:
✔ Clown location
✔ 120% urbanized
✔ Composite
✔ Adjusted twice
Thanks for the assist.
Image
Image
Read 5 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Don't want to be a Premium member but still want to support us?

Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal

Or Donate anonymously using crypto!

Ethereum

0xfe58350B80634f60Fa6Dc149a72b4DFbc17D341E copy

Bitcoin

3ATGMxNzCUFzxpMCHL5sWSt4DVtS8UqXpi copy

Thank you for your support!

Follow Us!

:(