SignalsSome formulaic patterns
Sentence-length variation32% variation
Human writing mixes short sentences with long ones. Machine drafts tend toward a uniform middle length. Higher variation reads more naturally.
Sentence lengths: 20, 8, 12, 14
Average sentence length13.5 words
Long average sentences make prose heavy regardless of who wrote it. Around 15-20 words reads comfortably; past 25 the reader starts working.
Overused vocabulary12 instances (222.2 per 1000 words)
A small set of words appears far more often in generated text than in human writing. Their density is the single most visible tell.
delve · leveraging · robust · seamless · crucial · myriad · facilitate · landscape · underscores · embark · holistic · comprehensive
Hedge phrases2 found
Phrases like "it is important to note that" add words without adding meaning. Cutting them shortens the text and sharpens it.
it is important to note · In today's fast-paced world
Em dash density0 dashes (0.0 per 1000 words)
Models punctuate with em dashes several times more often than people typing on a keyboard, where the character is awkward to reach.
Connective openers3 of 4 sentences
Sentences that begin Moreover, Furthermore, Additionally are connective throat-clearing. A few are fine; a pattern of them is a tell.
Moreover, leveraging robust frameworks is crucial for success. · Furthermore, this seamless approach will facilitate numerous outcomes … · Additionally, organisations should embark on a holistic transformation…
This is not an authorship verdict. No detector can reliably establish who or what wrote a text - OpenAI withdrew its own for low accuracy, and false positives fall hardest on people writing in a second language. These are measurements of the writing, not claims about the writer. Please do not use them to accuse anyone.
Low variation and heavy hedging are worth fixing whoever wrote the draft.Rewrite it with the humanizer
Category:ai
Mode:Offline
Version:1.0.0
Access:Free
AI检测器能够告诉你什么,也不能告诉你什么
该工具测量使散文读作机器生成的书写模式,并用其背后的证据报告每个。它不会输出模型写出您的文本的百分比机会,因为该数字无法诚实地产生,而且无论如何产生它的危害是真实的。
AI检测器的问题在这里,它们是统计分类器,从表面特征猜测作者身份,它们不够可靠,以至于OpenAI以低准确率撤回了自己的文章。它们的误报最难落在用第二语言写作的人身上,他们的散文明显更规律,因此对于分类器来说看起来更像机器。看起来自信的87%AI生成被用来指责学生或拒绝自由职业者,而且它下面没有任何东西可以承载这种重量。任何向您显示这样数字的工具都邀请您对抛硬币做出相应的决定。
诚实地衡量的是文本本身。句子长度变化通常称为突发性,是最强的单一信号:人类写作将三字句与三十字句混合在一起,而机器草稿则稳定为统一的中间长度。对于小组单词模型过度使用,词汇密度计算文本达到的频率。对冲密度计算诸如"值得注意的是"之类的短语,这些短语会增加长度而没有意义。 Em 破折号率计算字符模型产生的频率是输入者的几倍。连接开头的句子以"此外或进一步"开头。
些"每一个都是关于写作的事实,而不是关于作家的主张,并且每个都用产生它的匹配项来报告,所以你可以检查测量而不是信任它"这使得结果对于它实际上有益的东西很有用:编辑变异低和对冲重,无论是谁写的散文都更糟,而且两者都是可修复的。
Yong它来诊断自己的草稿, 看看文档的哪些部分读成公式, 了解其中的模式是什么, Bu要使用它, 也不要让任何人使用它, 来决定一个人是否在说出自己De工作真相, 所有的事情都在你的浏览器中运行;没有上传、记录或存储任何东西。
AI模式如何检查写作
1
粘贴文本
Any prose - 一份草稿,一篇文章,一份投稿,它留在你的浏览器中,永远不会上传。
2
读取每个信号
6个测量值,每个测量值都有其值,一个简单的英语解释,以及产生它的匹配项。
3
检查证据
每个信号都列出了它实际匹配的内容。如果计数看起来错误,证据就会告诉您原因。
4
修复什么值得修复
Low variation,重避险,谁写谁写的更差,把文字发给人性化者,或者手工编辑。
它衡量什么
句子长度变化(爆发性)
Reported为变异系数,所以不依赖于绝对长度,集合中最强的单信号。
过度使用的词汇密度
计算大约 40 个单词模型,每 1000 个单词不断标准化,因此短文本和长文本进行比较。
对冲和开仓计数
添加长度但没有意义的短语,以及以结缔清喉开头的句子,均以匹配列出。
每个数字的证据
每个信号都显示实际匹配或原始句子长度,因此可以检查而不是相信测量结果。
Frequently Asked Questions
No, 并且也不能有任何其他检测器, 无论它的输出看起来多么自信。这衡量的是书写模式, 而不是作者身份。把一个给你百分比的工具当作猜测, 因为它是。
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