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

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More from @orwell2022

Nov 11
1/ Deutschland, die Energienarren der Welt: Thread.

Hier ist die Preiskurve (31 Tage, stündlich). Kaufe teuer, verkaufe billig. Bottom Nailers (oder auch Narren). Angeblich importieren sie, weil es billiger ist? Nein. Die Sonne scheint eben nicht nachts. Image
2/ Quelle: Agora Energiewende – de facto der Familienbetrieb der Grünen. Man sieht sofort, was los ist: Deutschland, auf einem Irrweg, in bestem Stil echter Narren. Verkaufen billig, kaufen teuer, alles im Namen der „Rettung“. Klar, wer nachts Sonne braucht, zahlt eben drauf. Image
3/ Jetzt wierholen wir zusammen, wie echte Hofnarren:

„Importieren ist billiger“
„Schweden hat versagt“
„Lauterbach rettet Leben“
@roberthabeck for Chancellor. Ab hier anders. Image
Read 5 tweets
Oct 7
1/ The use of the BI (bigness index) to classify rural/urban areas is flawed. Landsat-derived GHSL BU (Global Human Settlement Layer Built-Up) data shows the rural curve (in green 🟩) consistently trailing the urbanized GHSL BU data (10% BU = typically for small towns 🟧). Image
2/ The Bigness Index (BI) is not only a poor parameter but outdated. Even Kabul Airport shows up with BI=0.

Shown below: GHCN stations labeled BI=0, highlighting those with 2% 🟠 and 10% 🔴 built-up areas in 2020 (from the EU-GHSL).

Image
3/ Analyzing further: nearly half of the stations are classified as rural (BI=0). This is complete nonsense, as the GHSL built-up percentages 2020 for these stations clearly indicate. Nearly all are, in fact, urban—which explains why they see no difference to officially urban. Image
Read 32 tweets
Oct 1
1/ Climate stripes - the origins.

Can we do better than Ed Hawkins? Yes, we can.

The perfect smoothed climate stripe, maximizing color pivot for ultimate fear manipulation.

Perfection—better than the original. Or in other words: how to manipulate your mind. Image
2/ Here’s how it’s done:

1 Pick a highly urban(izing) place: Stockholm.
2 Calculate anomaly.
3 Maximize range.
4 Apply LOESS for max color pivot (=mindfuck)

Note: UHI in Stockholm is ~2°C. Never mind that—the goal is to manipulate your minds.


Image
3/ Now let's try GOTHENBURG. Hold on a second... what's happening? It looks like we've accidently landed in the US Midwest—in the middle of nowhere, where hockey sticks don't flourish. Nice flatliner we have here, just like CHAMA.

Image
Read 4 tweets
Sep 10
They're trolling / insulting. The request was clear: compare ERA5 2km / @meteoblue with @AEMET_CValencia sensor at an hourly level. If they match at night, cloudy days, winter, but the sensor shows higher T in summer clear skies / no wind / day 👉 sensor is heat-biased. So? Go.
Thanks, @meteoblue. Normal conversation can be so easy. If the Spanish gentlemen would now provide access to their hourly station dataset, we can overlay it with the fine-grid ERA5 2km hourly product and see what's going on. Does that sound like a way forward @AEMET_CValencia ?

Image
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@meteoblue @AEMET_CValencia He clearly doesn’t understand their response nor my request. At this stage, I just want him to provide THE HOURLY DATA. What the answer actually means is that the 30 km cell is more representative of the region’s climate—yes, it’s better than the station. Well done @ChGefaell 👍.

Image
Image
Read 10 tweets
Sep 3
1/ Such places have no credibility for accurate bias free measurements. It's the opposite of a stable environment and per default a diesel powered urban expedition place. We see how the melting starts around the airport and the town.

How to measure? 👉 open.substack.com/pub/orwell2024…


Image
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2/ Here we see another example (Alaska). Russian high-lat regions are among the worst. It's a deception to take measurements from such places and claim that you've done 'science' while actually just picking up dirt. Why not Everest dirt basecamp next?
3/ It escalated quickly. Similar to @BMcNoldy from Miami, master's student @Daaanvdb also used airport data instead of professional equipment, like what's available at @UNISvalbard.

Let's do better and use proper data from a better looking station.


Image
Read 19 tweets
Jun 27
1/ As mentioned, Europe is too urbanized for climate measurements. Shown below is just the UHI effect. As mentioned, ANY type of urban landscape altering increases surface temperatures as well. The Netherlands and Benelux regions are all fully biased and unfit for climate science
Image
2/ As mentioned previously, North Sweden is the most credible place for climate measurements due to its development, peace, and ability to capture high-quality data. Besides Sweden, only the US provides reliable historic data. All other regions are not credible and biased today. Image
3/ Source: YCEO Surface Urban Heat Islands: Spatially-Averaged Daytime and Nighttime Intensity for Annual, Summer, and Winter.

It's from 2003. Now it's even more urbanized = worse.

developers.google.com/earth-engine/d…
Read 12 tweets

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