1/: Scientific integrity is a valuable commodity. What happens when external funders take influence on both scientific™ findings and media coverage can be seen in the current global crisis. It is time to return to the fundamental principles of science: ⬇️A thread⬇️
2/: In this thread, I will roughly explain why #empiricism and #repeatability are important factors for science and why model approaches should be interpreted with caution (and that is what I am saying as a modeller).
3/: I am aware that the principle of science is far more profound than explained in this thread, but this thread is written for laymen on @twitter and not for the lecture room. Also, within the scientific community, there is no clear consensus about this topic either.
4/: In recent years, I have been working on complex food production systems that increase food production and show high nutrient and water use efficiencies. I have thus been involved in plant growth experiments and holistic system modelling activities (@MATLAB, @AnyLogicCo).
5/: The plant growth experiments included environmental factors, #metagenomics (i.e. microbial genome sequencing), flow regulations etc. and the modelling covered the prediction on non-existing systems based on experimental and literature data.
6/: The IMHO most important principle of science is #empiricism. Empirical evidence is information that verifies the truth (which accurately corresponds to reality) or falsity (inaccuracy) of a claim. However, experiments and observations usually do not represent the "truth".
7/: There can be many intervening factors that have an impact on the observations. The less the conditions are controlled, the higher the deviations. So in order to “find the truth”, one wants to conduct an experiment in an environment with as few as possible inference factors.
8/: I will explain this through the example of my plant growth experiments. One can conduct the experiment in a greenhouse; solar radiation, humidity, temperature etc., are no stable factors. However, in a “climate chamber”, all of these factors can be standardized.
9/: This allows us to compare experiments with one another much easier. But there are also other factors that are not easy to control. These are (often) the genetic diversity of plant species, microbiological characteristics of the process water etc.
10/: This brings us to the point to talk about #repeatability. First of all, it’s essential that an experiment should contain several replications (or, if not possible repetitions) and control groups to ensure a high statistical relevance with respect to the made observations.
11/: However, the results are fundamentally dependent on the many factors, which have a decisive influence on the experiment’s outcome. I will give you two examples to explain what I mean: (a) my experiences with plant growth experiments; (b) vitamin D #COVID trials.
12/: In one experiment, we observed that lettuce grew much faster (40%) when being grown in aquaculture-derived water that contained many bacteria (i.e. which was not sterile such as it is the case for hydroponics systems). mdpi.com/2073-4441/8/10…
13/: I repeated this experiment in different locations repeatedly, and the results seem to differ (still, we always see a growth advantage). This has to do with environmental conditions, different microbial strains in the process water, different seed material/quality etc.
14/: So what’s the truth? I don’t know. Why don’t I know? Because it depends. What does it depend on? Well, many factors.

And plant growth experiment cannot be considered complex compared to the field of epidemiology or alike, where it’s even harder to control conditions.
15/: I was able to make similar observations regarding vitamin D studies. Many studies have been conducted in this field, and they are everything but uniform, also due to different hypotheses. An overview of conducted vitamin D studies can be found here: vdmeta.com
16/: In general, we can see that vitamin D has a high impact on the severity of the course of COVID, the death rate etc. And yet, meta-analyses generally compare apples and oranges (which is often unavoidable, so there is nobody to blame).
17/: The approach of every study differs in the following approaches: (1) amount IU of vitamin D administered; (2) time of administration; (3) physical characteristics of the patients; (4) selection of individuals; (5) dietary co-factors; etc. just to name some.
18/: There are, for example, studies out there that claim that vitamin D doesn't have an impact on COVID. Those studies, however, assume that a sufficient vitamin D blood serum level lays around 20 ng/mL, which is a completely faulty assumption. Still made it through peer review.
19/: Such drawn conclusions can cause confusions, and it’s the scientific community’s job to analyse, verify, and discuss findings. Such open discussions (which should include transparent peer-review processes) would help us to reduce biases.
20/: After having given you a brief insight into #empiricism and #repeatability, I want to talk about the field of modelling. During this 'pandemic', the outcome of models, again and again, justify political restrictions. But how does modelling work?
21/: The objective of a prediction model is to predict the future on the basis of available or predicted data. Often, complex situations have to be simplified for a model to work.
22/: In the last couple of months, we came across many modelled predictions: almost all of them were completely wrong (remark: don’t let physicists work in the field of epidemiology). Issues such as #seasonality have been purposely neglected, which is a methodological failure.
23/: Comparing the model prediction with the actual observations is called “model validation”. Every serious scientist should validate their models and publicly discuss why the model failed or was able to predict the future. This is somehow not the case anymore.
24/: It would be exciting to get to know why @ViolaPriesemann, @EricTopiol, @CorneliusRoemer, @neil_ferguson, or @VSPTUBerlin (who are traffic planners lol) do not validate their COVID-models but instead keep on publishing doomsday scenarios with their faulty work.
25/: It is also useful to illustrate complex relationships in so-called causal-loop diagrams prior to blindly modelling a situation. That is at least what I do (see graphic for Kombucha).
26/: A holistic causal loop diagram demonstrating the complexity of the pandemic environmental–health–socio–economic system can be found in this publication: mdpi.com/2079-8954/8/2/…. This could for example be a solid basis for a holistic model (consisting of several submodels).
27/: Every serious scientist should keep on questioning the “reality” and his/her own work. I can only recommend the mentioned “scientists” and many other modellers to read the following article. rapidinsight.com/blog/preventin…
28/: I also have another shout-out to the media: why do you keep on giving scientists a platform that have been wrong several times.
31/: … let their bachelor students do the modelling job…
32/: … lack of a scientific degrees…
33/: … make false statements… (plus get funded by #Soros, @wef and @WHO; i.e. conflict of interests)
34/: … defame genuine colleagues…
35/: … have conflicts of interests… (best wishes to the @gatesfoundation). etc.
36: Also, the #TeamScience that the media talks about is much bigger than assumed. Critical voices are disregarded or discredited. Instead, those who are in line with the agenda (no matter how unscientific their approach is) are presented as “THE SCIENCE™” we should listen to.
37/: Last but not least, John Ioannidis wrote one of the most important publications of the last decades about this topic: “Why Most Published Research Findings Are False”. Give it a go because he is part of the real #TeamScience. ncbi.nlm.nih.gov/pmc/articles/P…

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More from @goddeketal

3 Apr
1/: Characteristics of a normal reaction to a real pandemic would be: (1) promoting general #health, (2) protecting #vulnerable groups in particular, (3) avoiding spreading #panic, (4) applying scientifically proven #measures, etc. Instead, we observe the opposite. ⬇️A THREAD⬇️
2/: Usually, a problem constitutes the starting point of a pandemic scenario. Depending on the particular problem, a plan/strategy is developed that then is executed. During that execution, bugs/mistakes can appear. Thereupon we can observe results that can be evaluated.
3/: This evaluation should usually be unbiased. All observations must be taken into account. In case it did not lead to the desired outcome, a new plan might then be required, which can lead to various iterations.
Read 26 tweets
31 Mar
1/: This is the most disturbing video that I have seen since “2 girls 1 cup”. What's striking is that most of the partners of this misanthropic @laschools-initiative share the same wet dream: #eugenics. I will elaborate on this in this ⬇️small thread⬇️.
2/: As I have explained in my mega-thread below (read it!), #eugenics come hand in hand with science and politics. Just because it is claimed that there is a 'public or scientific consensus', it does not mean that those media reports represent reality.
3/: The partners of this @laschools' "Safe Steps to Safe Schools"-project can be seen below. Especially noticeable is the involvement of the nerd sweater's company @Microsoft and several universities that are financed by the @gatesfoundation.
Read 14 tweets
30 Mar
1/: The fate of the world as we know it is at stake. Pseudoscience is dominating the news. My appeal is based on the appendix of Michael Crichton's book ‘State of Fear’ that clarifies why politicised science is dangerous. It is more topical than ever. ⬇️a thread⬇️ Image
2/: Imagine a new ‘scientific theory’ that warns of an imminent crisis and points to a way out. This particular theory quickly draws support from mass media, leading scientists, politicians, and celebrities/influencers worldwide. independent.co.uk/life-style/cor…
3/: Research is funded by renowned philanthropists and carried out at prestigious universities and research institutes. The crisis is reported frequently in the media. This science is taught in college and high school classrooms. ImageImage
Read 56 tweets
21 Mar
1/: 𝐆𝐨𝐯𝐞𝐫𝐧𝐦𝐞𝐧𝐭𝐬: #StayHome

Staying inside leads to reduced direct sunlight exposure, which in turn has adverse effects on the #VitaminD levels.

The current 'pandemic' and its associated problems are homemade. The taken measures eventually do more harm than good. ⬇️
2/: What many people do not know is that vitamin D is an immunoregulatory hormone. The lower vitamin D levels, the more people will get sick. This has been a scientific consensus until the @who changed the definition of immunity in 2020.
3/: Motivating people to enjoy the sun, providing everybody with free vitamin D supplements, banning agro-toxins and industrial sugars, and stop testing asymptomatics will not only stop the pandemic but also increase both life quality and life expectancy. What are we waiting for?
Read 9 tweets
19 Mar
Justifications for government-mandated lockdown measures. Can't stop, won't stop.

🧵A thread. Image
It's just a rapid peer-review process.
Read 26 tweets
11 Mar
1/: I've been on a flight with @AirFranceKLM today. I experienced many illogical events that should create a climate of scepticism. Instead, the majority of society prefers to become a cowardly hanger-on who prefers to parrot the governments' narrative. ⬇️a short thread⬇️
2/: In order to travel to the #Netherlands by plane, I had to:

👉 have a negative PCR test taken within hours before the flight
👉 wear FFP2 masks during the 12h-flight
👉 have fever tested before entering and after leaving the plane
👉 enter 10 days of quarantine upon arrival
3/: At this point one needs to question the whole procedure. It's entirely irrational. Treating proven healthy individuals as highly infectious can't be good for the mental state of those who have difficulties assessing the whole situation.
Read 8 tweets

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