经典句子： 

 now if you think this is just a problem for psychology， neuroscience， or medicine， consider the pentaquark， an exotic particle made up of five quarks，as opposed to the regular three for protons or neutrons. particle physics employs particularly stringent requirements for statistical significance referred to as five sigma or one chance in 3.5 million of getting a false positive. but in 2002 a japanese experiment found evidence for the theta plus pentaquark and in the two years that followed, eleven other independent experiments then looked for and found evidence of that same pentaquark with very high levels of statistical significance. from July 2003 to may 2004, a theoretical paper on pentaquarks was published on average every other day, but alas it was a false discovery. further experimental attempts to confirm that theta plus pentaquark using greater statistical power failed to find any trace of its existence

如果您认为这只是心理学、神经科学或医学的问题，请考虑五夸克是由五个夸克组成的奇异粒子，而不是质子的常规三个夸克或中子。粒子物理学对统计显着性采用了特别严格的要求，即 5 西格玛或 350 万分之一的概率出现假阳性，但在 2002 年，日本的一项实验发现了 theta+ 五夸克的证据，并在随后的两年里进行了其他 11 个独立的实验。然后通过实验寻找并发现了具有非常高统计显着性的同样的五夸克的证据，从 2003 年 7 月到 2004 年 5 月，平均每隔一天就会发表一篇关于五夸克的理论论文，但可惜的是，这是一个错误的发现，进一步的使用更严格的统计，实验证实theta+ 五夸克，未能找到其存在的任何痕迹，

the problem was those first scientists weren't blind to the data. they knew how the numbers were generated and what answer they expected to get， and the way the data was cut and analyzed or P hacked produced the false finding. now most scientists aren't P hacking maliciously. there are legitimate decisions to be made about how to collect analyze and report data， and these decisions impact on the statistical significance of results

那些第一批科学家并不是对数据视而不见，他们太知道数字是如何生成的，他们期望得到什么答案，以及数据被切割和分析的方式 或 要得到所期望的P值而产生了错误的发现，大多数科学家都没有恶意操纵P值，有关于如何收集分析和报告数据才能做出合法的判断，这些判据影响统计显着性的结果，

scientists have huge incentives to publish papers in fact their careers depend on it

科学家有巨大的动力去发表论文，事实上，他们的职业生涯取决于发表论文

the thing I find most striking about the reproducibility crisis in science is not the prevalence of incorrect information in published scientific journals. after all, getting to the truth we know is hard and mathematically not everything that is published can be correct. what gets me is the thought that even trying our best to figure out what's true using our most sophisticated and rigorous mathematical tools, peer review, and the standards of practice， we still get it wrong so often. so how frequently do we delude ourselves when we're not using the scientific method. as flawed as our science may be, it is far and away more reliable than any other way of knowing that we have

这是我发现最引人注目的可重复性 科学危机并不是已发表的科学期刊中错误信息的普遍存在，毕竟要了解我们知道的真相是很困难的，而且从数学上讲，并不是所有已发表的内容都是正确的，让我感到困惑的是，即使我们尽了最大努力去弄清楚什么是真实的 使用我们最复杂和最严格的数学工具同行评审和实践标准，我们仍然经常出错，所以当我们不使用科学方法时，我们经常欺骗自己，我们更能肯定的是科学报导可能有缺陷.

视频文件：

Is Most Published Research Wrong1.mp4

Is Most Published Research Wrong.docx

出处：

https://www.youtube.com/watch?v=42QuXLucH3Q

Is Most Published Research Wrong?

More information on this topic: http://wke.lt/w/s/z0wmO

https://wakelet.com/wake/35a80e1c-0033-4db1-a5c1-28337f57d75b

The Preregistration Challenge: https://cos.io/prereg/

Resources used in the making of this video: Why Most Published Research Findings Are False: http://journals.plos.org/plosmedicine...

https://journals.plos.org/plosmedicine/article?id=10.1371%2Fjournal.pmed.0020124

Why Most Published Research Findings Are False

参考文献：

https://www.sohu.com/a/423577113_788170

https://zhuanlan.zhihu.com/p/389134254

诺奖得主本庶佑：CNS这些顶刊观点有九成不正确，不要盲从迷信，搞科研做到六个C更重要

https://www.163.com/dy/article/FEE1RTDF05419EOY.html

历史学家李伯重：无论何种“学术垃圾”，都是有害的，而且都是公害

扩展听力资料：

https://www.youtube.com/watch?v=bVG2OQp6jEQ

This is How Easy It Is to Lie With Statistics

https://www.youtube.com/watch?v=IwkPEAY4D1c

Your Favorite Research Is (Probably) Wrong: The Replicability Crisis

https://www.youtube.com/watch?v=VcgO2v3JjCU

Is Science Reliable?

https://www.youtube.com/watch?v=5xgbRxA_7DI

ACADEMIA IS BROKEN! The publishing scandal happening right now

https://www.youtube.com/watch?v=rPkBGe8XTAk

6 Publication Bias: Why Most Published Research Findings are False: Part I (FR)

https://www.youtube.com/watch?v=wM0vXVclQZg

"Why Most Published Research Findings are False" Part I

https://www.youtube.com/watch?v=NWjN67vqXOo

"Why Most Published Research Findings are False" Part II

https://www.youtube.com/watch?v=_GAeTwLB24c

"Why Most Published Research Findings are False" Part III

https://www.youtube.com/watch?v=dvk2PQNcg8w

Post-Truth: Why Facts Don't Matter Anymore

https://www.youtube.com/watch?v=7JwElC2pkkM

Fraud & Deception in Science | Elisabeth Bik, PhD

https://www.youtube.com/watch?v=QGWeVbYduOI

The scandal that shook psychology to its core

英汉对照（机器翻译）

in 2011 an article was published in the

2011年，

reputable Journal of Personality and

著名的《人格与

Social Psychology it was called feeling

社会心理学杂志》上发表了一篇文章，题为“感受

the future experimental evidence for

未来对

anomalous retroactive influences on

cognition and effect or in other words

认知和效果的异常追溯影响的实验证据”，换句话说，

proof that people can see into the

证明人们可以预见

future

未来，

the paper reported on nine experiments

该论文报告了九个实验

in one participants were shown two

一名参与者

curtains on a computer screen and asked

在电脑屏幕上看到两块窗帘，并被

to predict which one had an image behind

要求预测哪一块背后有图像，

it the other just covered a blank wall

另一名

once the participant made their

参与者在参与者做出选择后，将

selection the computer randomly

positioned an image behind one of the

图像随机放置在其中一个

curtains then the selected curtain was

窗帘后面，然后将所选窗帘覆盖在空白墙上。

pulled back to show either the image or

拉回以显示图像或

at the blank wall the images were

在空白墙上，

randomly selected from one of three

从三个类别之一中随机选择图像，

categories neutral negative or erotic if

中性负面或色情如果

participants selected the curtain

参与者选择

covering the image this was considered a

覆盖图像的窗帘，那么

hit now with there being two curtains

现在有两个窗帘

and the images positioned randomly

并且图像随机放置，这被认为是热门

behind one of them you would expect the

其中一张图片的

hit rate to be about 50% and that is

命中率约为 50%，这正是

exactly what the researchers found at

研究人员发现的，

least for negative and neutral images

至少对于负面和中性图像而言，

however for erotic images the hit rate

然而对于色情图像，命中

was 53% does that mean that we can see

率为 53%，这是否意味着我们可以预见

into the future is that a slight

未来 是一个轻微的

deviation significant well to assess

偏差，可以很好地评估显

significance scientists usually turn to

着性，科学家通常会转向

p-values a statistic that tells you how

p 值，这是一种统计数据，可以告诉您

likely a result at least this extreme is

if the null hypothesis is true in this

如果零假设为真，则至少出现这种极端结果的可能性有多大，在这种

case the null hypothesis would just be

情况下，零假设只是

that people couldn't actually see into

人们不能' 没有真正预见到

the future and the 53% result was due to

未来，53% 的结果是由于

Lucky guesses for this study the p-value

本研究的幸运猜测，p 值为

was 0.01 meaning there was just a 1%

0.01，这意味着只有 1% 的

chance of getting a hit rate of 53

机会

percent or higher from simple luck

从简单的运气中获得 53% 或更高的命中率

p-value is less than 0.05 are generally

p 值为 小于 0.05 通常被

considered significant and worthy of

认为是重要且值得

publication but you might want to use a

发表的，但在

higher bar before you accept that humans

您接受人类

can accurately perceive the future and

可以准确感知未来并

say invite the study's author on your

邀请该研究的作者参加您的

news program but hey it's your choice

新闻节目之前，您可能需要使用更高的标准，但嘿，毕竟这是您的选择

after all the point O 5 threshold was

5 阈值是

arbitrarily selected by Ronald Fisher in

Ronald Fisher 在

a book he published in 1925 but this

1925 年出版的一本书中任意选择的，但这

raises the question how much of the

提出了一个问题：

published research literature is

已发表的研究文献中有多少

actually false the intuitive answer

实际上是错误的，直观的答案

seems to be 5% I mean if everyone's

似乎是 5% 我的意思是，如果每个人都

using P less than 0.05 as our cutoff for

使用小于 0.05 的 P 作为我们的截止值 出于

statistical significance you would

统计显着性，您会

expect five of every hundred results to

期望每 100 个结果中有 5 个

be false positives but that

是误报，但

unfortunately grossly under

不幸的是，严重

estimates the problem and here's why

低估了问题，这就是为什么

imagine you're a researcher in a field

想象您是某个领域的研究人员，

where there are a thousand hypotheses

currently being investigated let's

目前正在研究 1000 个假设，让我们

assume that 10% of them reflect true

假设 10% 它们反映了真实的

relationships and the rest are false but

关系，其余的都是错误的，但

no one of course knows which are which

当然没有人知道哪个是哪个，这就是

that's the whole point of doing the

research now assuming the experiments

现在进行研究的全部意义，假设实验

are pretty well designed they should

设计得很好，他们应该

correctly identify around say 80 of the

正确地识别出

hundred true relationships this is known

一百种真实关系中的大约 80 种，这被称为

as a statistical power of 80% so twenty

统计功效为 80%，因此 20 个

results are false negatives perhaps the

结果为假阴性，可能是

sample size was too small or the

样本量太小，或者

measurements were not sensitive enough

测量结果不够敏感。

now consider that from those 900 false

现在考虑一下，从

hypotheses using a p-value of 0.05 45

使用 p 值为 0.05 的 900 个错误假设中，45 个

false hypotheses will be incorrectly

错误假设将被错误地

considered true as for the rest they

视为正确，如下所示 其余的

will be correctly identified as false

将被正确识别为虚假结果，

but most journals rarely published no

但大多数期刊很少发表任何

results they make up just 10 to 30

结果，它们仅占论文的 10% 到 30

percent of papers depending on the field

%，具体取决于领域，

which means that the papers that

这意味着

eventually get published will include 80

最终发表的论文将包括 80 个

true positive results 45 false positive

真阳性结果 45 个假阳性

results and maybe 20 true negative

结果 也许 20 个真实的阴性

results nearly a third of published

结果，即使系统正常工作，近三分之一的已发表

results will be wrong even with the

结果也会是错误的，

system working normally things get even

worse if studies are underpowered and

如果研究动力不足，并且

analysis shows they typically are if

分析显示，如果

there is a higher ratio of false to true

hypotheses being tested or if the

正在测试的假说与真假的比例较高，或者如果研究的动力不足，情况会变得更糟，情况通常会更糟

researchers are biased all of this was

研究人员

pointed out in a 2005 paper entitled why

在 2005 年发表的一篇题​​为《为什么

most published research is false so

大多数发表的研究都是错误的》的论文中指出了所有这一切，因此

recently researchers in a number of

最近许多领域的研究人员

fields have attempted to quantify the

试图通过复制过去

problem by replicating some prominent

一些突出的

past results the reproducibility project

结果来量化这个问题。可重复性项目

repeated 100 psychology studies but

重复了 100 项心理学研究，但

found only 36% had a statistically

发现 第二次只有 36% 的结果具有统计

significant result the second time

显着性，

around and the strength of measured

测量到的

relationships were on average half those

关系强度平均为

of the original studies an attempted

原始研究的一半，尝试

verification of 53 studies considered

验证 53 项被认为具有

the landmarks and the basic science of

里程碑意义的研究，即使密切合作，癌症基础科学也只能

cancer only managed to reproduce six

重现 6 项研究

even working closely with the original

对于原始

study's authors these results are even

研究的作者来说，这些结果

worse than I just calculated the reason

比我刚刚计算的结果还要糟糕，

for this is nicely illustrated by a 2015

2015 年的一项研究很好地说明了其原因，该

study showing that eating a bar of

研究表明每天吃一块

chocolate every day can help you lose

巧克力可以帮助您

weight faster in this case the

更快地减肥，在这种情况下，

participants were randomly allocated to

参与者被随机分配到

one of three treatment groups one went

一个 三个治疗组中，一组

on a low-carb diet

采用低碳水化合物饮食，

another went on the same low-carb

另一组采用相同的低碳水化合物饮食，

plus a one point five ounce bar of

chocolate per day and the third group

每天加一点五盎司的巧克力，第三组

was the control instructed just to

是对照组，指示在治疗

maintain their regular eating habits at

the end of three weeks the control group

结束时保持正常的饮食习惯。 三周后，对照组的

had neither lost nor gained weight

体重既没有减轻也没有增加，

but both low-carb groups have lost an

但两个低碳水化合物组

average of five pounds per person the

每人平均减轻了五磅，但

group that ate chocolate however lost

吃巧克力的组比

weight ten percent faster than the non

不吃巧克力的组减轻了百分之十的速度，

chocolate eaters the finding was

这一发现具有

statistically significant with a p-value

统计学意义，p  -值

less than 0.05 as you might expect this

小于 0.05，正如您所预料的那样，这条

news spread like wildfire to the front

消息像野火一样传到了欧洲

page of build the most widely circulated

发行量最广的

daily newspaper in Europe and then to

日报的头版，然后传到了《

The Daily Star the Irish Examiner -

每日星报》、《爱尔兰观察家报》、《赫芬

Huffington Post and even shape magazine

顿邮报》，甚至是《形状》杂志，

unfortunately the whole thing had been

不幸的是，整个事情都被报道了

faked

kind of I mean researchers did perform

我的意思是研究人员

the experiment exactly as they described

确实按照他们描述的那样进行了实验，

but they intentionally designed it to

但他们故意设计它以

increase the likelihood of false

增加误报的可能性，

positives the sample size was incredibly

样本量非常

small just five people per treatment

小，每个治疗组只有 5 个人，

group and for each person 18 different

每个人跟踪了 18 种不同的测量

measurements were tracked including

结果，包括

weight cholesterol sodium blood protein

体重胆固醇 钠、血液蛋白质

levels sleep quality well-being and so

水平、睡眠质量、幸福感等等，

on so if weight loss didn't show a

所以如果体重减轻没有显示出显

significant difference there were plenty

着差异，那么可能还有

of other factors that might have so the

很多其他因素，所以

headline could have been chocolate

标题可能是巧克力

lowers cholesterol or increases sleep

降低胆固醇或提高睡眠

quality or something the the point is a

质量或其他重点

p-value is only really valid for a

p 值仅对

single measure once you're comparing a

单个测量值真正有效，一旦您比较了

whole slew of variables the probability

一大堆变量，

that at least one of them gives you a

其中至少一个变量给出

false positive goes way up and this is

误报的概率就会大幅上升，这就是

known as P hacking researchers can

所谓的“P黑客”研究人员可以

make a lot of decisions about their

做一个 有关分析的许多决策

analysis that can decrease the p-value

可能会降低 p 值，

for example let's say you analyze your

例如，假设您分析

data and you find it nearly reaches

数据，发现它几乎达到

statistical significance so you decide

统计显着性，因此您决定

to collect just a few more data points

收集更多数据点，

to be sure

以确定

then if the p-value drops below 0.05 you

p 值是否下降 低于 0.05 时，您

stop collecting data confident that

会停止收集数据，并确信

these additional data points could only

have made the result more significant if

如果确实存在真正的关系，这些额外的数据点只会使结果更加显着，

there were really a true relationship

there but numerical simulations show

但数值模拟表明，

that relationships can cross the

significance threshold by adding more

data points even though a much larger

即使样本更大，通过添加更多数据点，关系也可以跨越显着性阈值

sample would show that there really is

会表明确实

no relationship in fact there are a

没有关系，事实上有

great number of ways to increase the

很多方法可以增加

likelihood of significant results like

显着结果的可能性，例如

having two dependent variables adding

让两个因变量添加

more observations controlling for gender

更多观察结果来控制性别

or dropping one of three conditions

或放弃三个条件之一，将

combining all three of these strategies

所有这三种策略结合

together increase

在一起增加显着结果的可能性

the likelihood of a false positive to

假阳性的可能性

over 60% and that is using P less than

超过 60%，即现在使用小于

0.05 now if you think this is just a

0.05 的 P，如果您认为这只是

problem for psychology neuroscience or

心理学、神经科学或

medicine consider the pentaquark an

医学的问题，请考虑

exotic particle made up of five quarks

五夸克是由五个夸克组成的奇异粒子，

as opposed to the regular three for

而不是质子的常规三个夸克

protons or neutrons particle physics

或中子粒子物理学对

employs particularly stringent

requirements for statistical

统计显着

significance referred to as five sigma

性采用了特别严格的要求，即 5 西格玛

or one chance in 3.5 million of getting

或 350 万分之一的概率出现

a false positive but in 2002 a japanese

假阳性，但在 2002 年，日本的一项

experiment found evidence for the theta

实验发现了 theta

plus pentaquark and in the two years

加五夸克的证据，并在随后的两年里进行了

that followed eleven other independent

其他 11 个独立的实验。

experiments then looked for and found

然后实验寻找并发现了具有

evidence of that same pentaquark with

very high levels of statistical

非常高统计

significance from July 2003 to may 2004

显着性的同一个五夸克的证据，从 2003 年 7 月到 2004 年 5 月，

a theoretical paper on pentaquarks was

published on average every other day but

平均每隔一天就会发表一篇关于五夸克的理论论文，但

alas it was a false discovery further

可惜的是，这是一个错误的发现，进一步的

experimental attempts to confirm that

实验试图证实

theta plus pentaquark using greater

theta 再加上五夸克使用更大的

statistical power failed to find any

统计能力未能找到

trace of its existence the problem was

其存在的任何痕迹，问题是

those first scientists weren't blind to

那些第一批科学家并不是对

the data they knew how the numbers were

数据视而不见，他们知道数字是如何

generated and what answer they expected

生成的，他们期望得到什么答案，

to get and the way the data was cut and

以及数据被切割和

analyzed or P hacked produced the false

分析的方式 或 P 黑客攻击产生了错误的

finding now most scientists aren't P

发现，现在大多数科学家都没有

hacking maliciously there are legitimate

恶意黑客攻击，

decisions to be made about how to

关于如何

collect analyze and report data and

收集分析和报告数据需要做出合法的决定，

these decisions impact on the

这些决定会影响

statistical significance of results for

结果的统计显着性，

example 29 different research groups

例如 29 个不同的研究小组

were given the same data and asked to

被给予 使用相同的数据，并被要求

determine if dark-skinned soccer players

确定深色皮肤的足球运动员

are more likely to be given red cards

是否更有可能被红牌罚下，

using identical data some groups found

一些小组发现

there was no significant effect while

没有显着影响，而

others concluded dark-skinned players

另一些小组则得出结论，深色皮肤的足球运动员

were three times as likely to receive a

收到

red card the point is that data doesn't

红牌的可能性是该点的三倍 数据

speak for itself it must be interpreted

本身并不能说明问题，必须根据

looking at those results it seems that

这些结果进行解释，似乎

dark-skinned players are more likely to

深色皮肤的球员更有可能

get red carded but certainly not three

被红牌罚下，但

times as likely consensus helps in this

在这种情况下，共识的帮助肯定不是三倍，

case but for most results only one

但对于大多数结果来说，只有一项

research group provides the analysis and

研究 小组提供了分析，

therein lies the problem of incentives

其中存在激励问题，

scientists have huge incentives to

科学家有巨大的动力去

publish papers in fact their careers

发表论文，事实上，他们的职业生涯

depend on it as one scientist Brian no

依赖于此，正如美国证券交易委员会（SEC）一位科学家布赖恩（Brian no

SEC puts it there is no cost to getting

SEC）所说，犯错是没有成本的，

things wrong the cost is not getting

代价是不让

them published journals are far more

他们发表期刊。 更有

likely to publish results that reach

可能发表达到

statistical significance so if a method

统计显着性的结果，因此，如果

of data analysis results in a p-value

数据分析方法的 p 值

less than 0.05 then you're likely to go

小于 0.05，那么您很可能会

with that method publications also more

采用该方法

likely if the result is novel and

如果结果新颖且

unexpected this encourages researchers

出乎意料，那么您也更有可能发表论文，这会鼓励研究人员

to investigate more and more unlikely

去研究越来越多不太可能的

hypotheses which further decreases the

假设，这些假设进一步降低了现在测试的

ratio of true to spurious relationships

真实与虚假关系的比率，

that are tested

now what about replication isn't science

复制是不是科学

meant to self-correct by having other

意味着通过让其他

scientists replicate the findings of an

科学家复制

initial discovery in theory yes but in

最初发现的结果来进行自我纠正，理论上是的，但在

practice it's more complicated like take

实践中 更复杂的是，就像

the precognition study from the start of

从本视频开始进行的预知研究一样，

this video three researchers attempted

三名研究人员试图

to replicate one of those experiments

复制其中一个实验，

and what did they find

他们发现了什么，令人惊讶

well surprise surprise the hit rate they

obtained was not significantly different

的是，他们获得的命中率与

from chance when they tried to publish

他们试图

their findings in the same journal as

在 与

the original paper they were rejected

原始论文相同的期刊，他们被拒绝的

the reason the journal refuses to

原因是该期刊拒绝

publish replication studies so if you're

发表复制研究，所以如果你是

a scientist the successful strategy is

一名科学家，成功的策略很

clear and don't even attempt replication

明确，甚至不要尝试复制

studies because few journals will

研究，因为很少有期刊会

publish them and there is a very good

发表它们，而且有一个非常

chance that your results won't be

无论如何，你的结果很可能不会具有

statistically significant anyway in

统计显着性，在

which case instead of being able to

这种情况下，

convince colleagues of the lack of

reproducibility of an effect you will be

你不会被指责为没有正确执行，而不是能够让同事相信效果缺乏可重复性，

accused of just not doing it right so a

因此

far better approach is to test novel and

更好的方法是测试新颖的和

unexpected hypotheses and then P hack

your way to a statistically significant

result now I don't want to be too

我不想

cynical about this because over the past

对此过于愤世嫉俗，因为在过去的

10 years things have started changing

10 年里，事情已经开始变得

for the better

更好，

many scientists acknowledge the problems

许多科学家承认了

I've outlined and are starting to take

我概述的问题，并正在开始 为了采取

steps to correct them there are more

措施纠正这些问题，

large-scale replication studies

undertaken in the last 10 years plus

在过去 10 年里进行了更大规模的复制研究，此外

there's a site retraction watch

还有一个网站撤回观察，

dedicated to publicizing papers that

专门用于公布已

have been withdrawn there are online

撤回的论文，有在线

repositories for unpublished negative

存储库来存储未发表的负面

results and there is a move towards

结果，并且有提交假设的趋势

submitting hypotheses and methods for

peer review before conducting

在进行实验之前进行同行评审的方法，

experiments with the guarantee that

保证只要遵循

research will be published regardless of

results so long as the procedure is

程序，无论结果如何，研究都会被发表，

followed this eliminates publication

这消除了发表

bias promotes higher powered studies and

偏见，促进了更高水平的研究，并

lessens the incentive for pee hacking

减少了小便黑客的动机，

the thing I find most striking about the

这是我发现最引人注目的可

reproducibility crisis in science is not

重复性 科学危机并不是

the prevalence of incorrect information

in published scientific journals after

已发表的科学期刊中错误信息的普遍存在，毕竟要

all getting to the truth we know is hard

了解我们知道的真相是很困难的，而且从

and mathematically not everything that

数学上讲，并不是所有已

is published can be correct what gets me

发表的内容都是正确的，让我感到困惑的是，即使我们

is the thought that even trying our best

尽了最大努力去

to figure out what's true using our most

弄清楚什么是真实的 使用我们最

sophisticated and rigorous mathematical

复杂和最严格的数学

tools peer review and the standards of

工具同行评审和

practice we still get it wrong so often

实践标准，我们仍然经常出错，

so how frequently do we delude ourselves

所以

when we're not using the scientific

当我们不使用科学

method as flawed as our science may be

方法时，我们经常欺骗自己，因为我们的科学可能有缺陷，这

it is far and away more reliable than

是遥远的事情 比

any other way of knowing that we have

任何其他方式都更可靠，我们知道

this episode of veritasium was supported

这一集的 veritasium

in part by these fine people on patreon

部分得到了 patreon 上这些优秀人士

and by audible.com the leading provider

和 audible.com 的支持，audible.com 是领先的

of audiobooks online with hundreds of

在线有声读物提供商，拥有包括小说、非小说

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为任何观看此频道的人提供 30 天免费试用，

channel just go to audible.com slash

只需访问 audible.com 斜线

potasium so they know I sent you a book

钾，这样他们就知道我给你寄了一本书，

I'd recommend it is called the invention

我推荐这本书叫《

of nature by Andrea Wolfe which is a

自然的发明》，作者是 Andrea Wolfe，这是一本

biography of Alexander von Humboldt an

传记 亚历山大·冯·洪堡 (Alexander von Humboldt) 是一位

adventurer and naturalist who actually

冒险家和博物学家，实际上

inspired Darwin to board the Beagle you

启发了达尔文 (Darwin) 登上小猎犬号 (Beagle)。您

can download that book or any other of

可以在 audible.com 下载该书或

your choosing for a one-month free trial

您选择的任何其他书籍，免费试用一个月。

at audible.com slash veritasium so as

因此，

always I want to thank audible for

一如既往，我要感谢 audible 对

supporting me and I really want to thank

我的支持 我真的很感谢

you for watching

你的观看