docs(10_Wiki): Topic_Business/General/Graphic/Programming을 Topics/ 하위로 이동
최상위 10_Wiki/Topic_*였던 4개 카테고리 폴더를 10_Wiki/Topics/Topic_* 로 재배치. 콘텐츠 변경 없음(순수 폴더 이동) — Topics/ 하위 나머지 폴더는 이미 지난 커밋에서 전부 정리된 상태(잔존 항목은 에이전트 운영 상태 및 사용자가 보존을 요청한 업데이트0615/무제 3.canvas 뿐).
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Antigravity Agent
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---
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id: wiki-2026-0508-scientific-communication
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title: Scientific Communication
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category: 10_Wiki/Topics
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status: verified
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canonical_id: self
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aliases: [Science Writing, Research Communication, Academic Writing]
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duplicate_of: none
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source_trust_level: A
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confidence_score: 0.9
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verification_status: applied
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tags: [writing, research, papers, talks, ai-aided-drafting]
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raw_sources: []
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last_reinforced: 2026-05-10
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github_commit: pending
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tech_stack:
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language: english
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framework: LaTeX
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---
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# Scientific Communication
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## 매 한 줄
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> **"매 result 의 가치는 매 communication 의 quality 에 bound — 매 unread paper 는 0 impact"**. 매 origin 은 1665 Philosophical Transactions 의 letter format; 매 modern state 는 IMRaD structure, preprint culture (arXiv, bioRxiv), open peer review, 그리고 매 AI-aided drafting (Claude Opus 4.7 의 paper review + outline).
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## 매 핵심
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### 매 IMRaD 구조 (paper)
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- **Introduction**: 매 gap → 매 question → 매 contribution.
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- **Methods**: 매 reproducible (data, code, hyperparams).
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- **Results**: 매 figures + tables, 매 narrative.
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- **Discussion**: 매 implication, limitation, future work.
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### 매 audience layer
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- **Title**: 매 1-line — 매 99% 의 reader 가 only 보는 것.
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- **Abstract**: 매 250 words — 매 hook + result + implication.
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- **Figure 1**: 매 reader-grabbing visual.
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- **Body**: 매 0.5% 의 deep reader.
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### 매 modern delivery
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- **Preprint**: arXiv (cs/stat/ml), bioRxiv, OSF — 매 priority claim.
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- **Conf talk**: 15min + Q&A — 매 pyramid (conclusion first).
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- **Twitter/X thread**: 매 paper drop 시 1 thread = 매 5x download.
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- **Blog post**: 매 distill.pub-style — 매 interactive.
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- **Video**: 매 5-min explainer (CVPR/NeurIPS 의 supplementary).
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### 매 응용
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1. Research paper writing.
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2. Grant proposal.
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3. Conference talk.
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4. Tech blog (engineering science).
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## 💻 패턴
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### 매 LaTeX paper skeleton (NeurIPS 2026 style)
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```latex
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\documentclass{article}
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\usepackage[final]{neurips_2026}
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\usepackage{graphicx, amsmath, hyperref, cleveref}
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\usepackage[capitalize, noabbrev]{cleveref}
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\title{<Catchy Title: Method on Task with Number\%>}
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\author{Alice Smith \\ Acme Lab \\ \texttt{alice@acme.com}}
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\begin{document}
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\maketitle
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\begin{abstract}
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We address <gap>. We propose <method>. On <benchmark>, our approach
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achieves <X\%> ($\Delta$+Y\% over prior best). Code: \url{...}.
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\end{abstract}
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\section{Introduction}
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\input{sections/intro}
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\section{Method}
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\input{sections/method}
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\section{Experiments}
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\input{sections/experiments}
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\section{Related Work}
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\input{sections/related}
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\section{Conclusion}
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\input{sections/conclusion}
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\bibliographystyle{plainnat}
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\bibliography{refs}
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\end{document}
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```
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### 매 abstract template (250 words, 매 6-sentence hook)
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```text
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1. [Context] <Field> has long pursued <goal>.
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2. [Gap] However, existing methods <limit>.
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3. [Insight] We observe that <key insight>.
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4. [Method] Building on this, we propose <method>:
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<2-sentence description>.
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5. [Result] On <benchmark>, our method achieves <X%>,
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improving over <baseline> by <Δ>.
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6. [Impact] This suggests <broader implication> and
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enables <downstream application>.
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```
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### 매 figure 1 ("teaser" — 매 abstract 의 visual)
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```text
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매 좋은 figure 1 의 5 rule:
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1. 매 self-contained — caption 만 읽고 message 이해 가능.
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2. 매 axes labeled, units 명시.
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3. 매 baseline + ours comparison (color-blind safe).
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4. 매 ≤ 3 message — 매 더 많으면 split.
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5. 매 vector format (PDF) — 매 raster 의 X.
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```
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### 매 talk pyramid (15-min conf talk)
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```text
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00:00 — Hook (1 slide, 매 result tease)
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01:00 — Problem (2 slides, 매 why care?)
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03:00 — Insight (1 slide, 매 핵심 idea)
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04:00 — Method (3-4 slides, 매 just enough)
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08:00 — Results (3-4 slides, 매 main + ablation)
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12:00 — Limitation (1 slide, 매 honest)
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13:00 — Take-aways (1 slide, 매 3 bullets)
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14:00 — Q&A
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```
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### 매 Twitter/X thread 의 paper drop
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```text
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1/ 매 [TL;DR] — 매 1 sentence + result number + figure.
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2/ Why does this matter? (매 problem framing)
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3/ Insight (매 1 핵심 idea, 매 figure)
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4/ How (매 architecture, 매 다이어그램)
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5/ Results (매 main number, 매 baseline 대비)
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6/ Limitations (매 honest)
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7/ Code + paper + colab links.
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```
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### 매 Claude Opus 4.7 paper-review prompt (1M ctx, 매 full paper)
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```python
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import anthropic
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client = anthropic.Anthropic()
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paper_pdf_text = open("draft.txt").read() # 매 full paper
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msg = client.messages.create(
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model="claude-opus-4-7",
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max_tokens=8192,
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system=(
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"You are a senior NeurIPS reviewer. Review this paper:\n"
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"1. Summary (3 sentences).\n"
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"2. Strengths (3 bullets).\n"
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"3. Weaknesses (3 bullets, specific section refs).\n"
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"4. Questions for authors (3).\n"
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"5. Score (1-10) with justification.\n"
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"Be specific, cite line numbers, no generic praise."
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),
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messages=[{"role": "user", "content": paper_pdf_text}],
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)
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print(msg.content[0].text)
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```
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### 매 distill-style explainer (interactive, 매 React + MDX)
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```tsx
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// 매 D3 + MDX 로 매 inline interactive figure
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import { useState } from "react";
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import { MathJax } from "better-react-mathjax";
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export const TempScaling = () => {
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const [T, setT] = useState(1.0);
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return (
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<div>
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<p>Temperature <code>T={T.toFixed(2)}</code></p>
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<input type="range" min={0.1} max={5} step={0.1}
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value={T} onChange={e => setT(+e.target.value)} />
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<SoftmaxPlot T={T} />
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<MathJax>{`$$p_i = \\frac{e^{z_i/T}}{\\sum_j e^{z_j/T}}$$`}</MathJax>
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</div>
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);
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};
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```
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## 매 결정 기준
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| 상황 | Approach |
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| 매 conference paper | IMRaD + LaTeX + arXiv preprint |
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| 매 industry blog | distill-style + interactive figures |
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| 매 talk (15 min) | pyramid: conclusion → method → results |
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| 매 social drop | thread 7-tweet + figure 1 + code link |
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| 매 grant | story arc: problem → impact → method → milestones |
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**기본값**: paper 면 IMRaD + arXiv + 1-thread X drop + Claude Opus 4.7 self-review.
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## 🔗 Graph
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- 부모: [[Research Methodology]] · [[Technical Writing]]
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## 🤖 LLM 활용
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**언제**: 매 abstract 의 6-sentence drafting. 매 paper self-review (Claude Opus 4.7 1M ctx). 매 X thread draft. 매 grammar/clarity pass.
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**언제 X**: 매 result fabrication. 매 method 의 invention. 매 LLM 의 "novel contribution" claim.
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## ❌ 안티패턴
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- **Methods-section first sentence**: 매 reader 가 not knowing 'why' 도착. 매 motivation lead.
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- **Equation salad**: 매 prose 없이 equation 만 — 매 narrative 필요.
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- **Result-only abstract**: 매 context 없이 number 만.
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- **AI-generated filler**: 매 reviewer 가 매 hallmark detect.
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- **Buried lead**: 매 main result 가 page 8 — 매 figure 1 으로.
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## 🧪 검증 / 중복
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- Verified (Mensh & Kording "Ten simple rules for structuring papers", Pinker "Sense of Style", NeurIPS guidelines).
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- 신뢰도 A.
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## 🕓 Changelog
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| 날짜 | 변경 |
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|---|---|
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| 2026-05-08 | Phase 1 |
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| 2026-05-10 | Manual cleanup — IMRaD + LaTeX + Claude Opus 4.7 review + distill |
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