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医学研究者“发现”积分，获 75 次引用
Medical researcher discovers integration, gets 75 citations
2010 — 2021，它一次次回到首页
黑点是上首页（≥ 50 分）的那次投稿，空心点是没冲上去的投稿，点越大分数越高。
导读
博主翻到一篇 1994 年的医学论文，作者“独立发现”了数学中早已众所周知的梯形积分法，并将其命名为“Tai 模型”，该论文竟获得 75 次引用。文章借此调侃部分医学研究者对基础数学工具的陌生，也引发关于跨学科知识隔阂的讨论。
为什么经久不衰：它揭示了学术圈“重新发明轮子”和引用惯性的荒诞现象，提醒读者基础知识在跨学科应用中的价值，多年来反复引发共鸣。
HN 评论精选
医学从业者习惯被动接受和转述信息，缺乏追问和质疑的习惯
作者批评医学生靠死记硬背学物理，这让我想起一位产科医生朋友说“婴儿平均在凌晨 3 点出生”。我兄弟追问：24 小时制下“平均”是什么意思？我补充说这和平均风向是同类问题——把时间或角度当普通数字直接求平均会得到无意义的结果。而这位医生朋友显然完全退出了对话，她的世界里信息只是被接收、记录、转述，追根溯源和质疑并不是她的乐趣。
dmlorenzetti查看英文原文
The author calls out med students for approaching physics through rote memorization. It reminds me of an experience my older brother and I had with a doctor friend. Our friend, an OB/GYN, mentioned how hard her work is, because "the average baby is born at 3am." We laughed, but then my brother asked, "What does 'average' mean when you have a 24-hour clock? It must mean the modal time or something like that." I contributed that this is an issue in defining average wind directions, as well. The basic problem is that if you record times on a 0-24 hour scale, or wind directions on a 0-360 degree scale, and then naively average the numbers, you get meaningless results (for example, 180 degrees if the wind steadily rotates through every point of the compass). A quick glance at our doctor friend showed she had checked out of the conversation entirely. Possibly she just felt slighted that we were not bowing down in awe at the terrible hours she keeps. But my main impression was that she lives in a world where one receives a piece of information, notes it, and stores it away. And when repeating that received information, one's listeners duly note and store it away. Chasing down the source of the information, calling it into question, relating it to other things in the world-- these just weren't things she seemed to find pleasurable.
“重新发明轮子”人人都会犯，程序员也不例外，难在意识到自己不知道什么
要不是我自己也经历过无数次，我会笑得更响。程序员尤其容易犯这种错：谁没写过四页的 case 语句，而三行递归就能解决？不过我从没用自己的名字给 case 语句命名。再聪明的人也很难知道自己不知道什么，有时在一个领域越精通，反而越难想到另一个领域的现成方法。
noonespecial查看英文原文
I'd laugh a lot harder when people struggle for days and then reach a half-assed piece of some algorithm that's completely well know if I hadn't been there a dozen times myself. Programmers are especially vulnerable to this. Who hasn't made a 4 page case statement when 3 lines of recursion would have done it, especially when starting out? Then again, I've never named my case statements after myself. No matter how brilliant one is, its ridiculously hard to know what you don't know. In fact, sometimes being very advanced in one field makes it doubly hard to think of in one you're poor in.
身为医生证实了文中现象：医学界会把平凡推导当作成果命名
我是主修物理出身的医生，同意这篇文章。看这些人在生理学里推导公式简直煎熬——物理学家连注意都不会注意的推导中间步骤，他们却能以此留名。HN 和 Python 成了我的团体治疗和秘密瘾品。
niels_olson查看英文原文
I'm a doctor who majored in physics, and I agree with this post. Watching these folks come up with formulas in physiology was excruciating. People get their names on things that physicists wouldn't even bother noticing as something other than a single step in a derivation. Hacker News and Python have been come my group therapy and secret addiction, respectively.
75 次引用反映的是学术引用的路径依赖，而非 75 个人都不懂积分
要指出的是，那 75 次引用并不等于 75 个不懂积分的糊涂人。如果你写糖尿病论文想用积分分析，即使完全清楚其原理，也得论证方法对糖尿病的适用性。直接写“按 Tai 等人的方法”省事得多。这种“某某大牛也这么用，所以我们也用”的现象很常见。
stuartbman查看英文原文
I think it's important to note why the 75 citations isn't just 75 dummies who also haven't heard of integration. If you're writing a diabetes paper and want to use integration for your analysis (even if you are fully aware of its background), you'll be forced to justify your approach and defend it's applicability to diabetes. Far easier to say 'as per Tai et al...' and take it as given. You see this a lot- 'we used [x] because Big Name Prof did as well [citation]'
该论文已成为同行评审失效的著名案例
有趣的是，这篇论文被维基百科“学术同行评审”条目的“失败案例”一节引用了。
Cu3PO42查看英文原文
Amusingly this paper is cited in the "Failures" section of Wikipedia's article on "Scholarly peer review": https://en.wikipedia.org/?curid=33158412#cite_ref-Tai_1a_165-0
当事人回应：模型是独立摸索的常识，命名并非刻意邀功
下一期期刊刊登了一批指出她重新发现梯形法则的来信。Mary Tai 本人回应说：1981 年在哥伦比亚大学写博士论文时需要计算曲线下面积，在与统计顾问讨论后自己琢磨出了这个模型，其背后的概念是常识，无需查阅梯形法则。她称从未想把它当伟大发现发表，因同事使用并称之为“Tai 公式”，后因无法引用未发表成果才应要求投稿，名字是被“盖章”上去的。
vilhelm_s查看英文原文
In the next issue, the journal published a bunch of letters noting that she had rediscovered the trapezoid rule. https://kconrad.math.uconn.edu/math1132s20/handouts/taicomments.pdf Mary Tai herself also replied and explained the background to the paper a bit more: > While a doctoral candidate working on my dissertation at Columbia University in 1981, I needed to calculate total area under a curve. During a session with my statistical advisor, and after examining several alternative methods, I worked out the model in front of him. The concept behind it is obviously common sense, and one does not have to consult the trapezoid rule to figure it out. [...] > Why I call it Tai's model. I never thought of publishing the model as a great discovery or accomplishment; it was not published until 14 years later, in 1994. Because of its accuracy and easy application, many collegues at the Obesity Research Center of St Luke's-Roosvelt Hospital Center and Columbia University began using it and addressed it as "Tai's formula" to distinguish it from others. Later, because the investigators were unable to cite an unpublished work, I submitted it for publication at their request. Therefore, my name was rubber-stamped on the model before its publication. [...]
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