f8b21af4be
10_Wiki/Topics 대규모 정리: - 오류 캡처/미완성 stub 문서 227개 제거 - 교차폴더 중복 43클러스터 병합 (63파일 → redirect) - 링크명 정규화: 깨진 링크 수정·redirect 직결·개념 매핑 ~2,400건 - 카테고리 MOC 6개 신규 생성 - Graph 섹션 미해결 related-keyword 링크 10,058건 제거 Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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id, title, category, status, canonical_id, aliases, duplicate_of, source_trust_level, confidence_score, verification_status, tags, raw_sources, last_reinforced, github_commit, tech_stack
| id | title | category | status | canonical_id | aliases | duplicate_of | source_trust_level | confidence_score | verification_status | tags | raw_sources | last_reinforced | github_commit | tech_stack | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| wiki-2026-0508-scientific-communication | Scientific Communication | 10_Wiki/Topics | verified | self |
|
none | A | 0.9 | applied |
|
2026-05-10 | pending |
|
Scientific Communication
매 한 줄
"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).
매 핵심
매 IMRaD 구조 (paper)
- Introduction: 매 gap → 매 question → 매 contribution.
- Methods: 매 reproducible (data, code, hyperparams).
- Results: 매 figures + tables, 매 narrative.
- Discussion: 매 implication, limitation, future work.
매 audience layer
- Title: 매 1-line — 매 99% 의 reader 가 only 보는 것.
- Abstract: 매 250 words — 매 hook + result + implication.
- Figure 1: 매 reader-grabbing visual.
- Body: 매 0.5% 의 deep reader.
매 modern delivery
- Preprint: arXiv (cs/stat/ml), bioRxiv, OSF — 매 priority claim.
- Conf talk: 15min + Q&A — 매 pyramid (conclusion first).
- Twitter/X thread: 매 paper drop 시 1 thread = 매 5x download.
- Blog post: 매 distill.pub-style — 매 interactive.
- Video: 매 5-min explainer (CVPR/NeurIPS 의 supplementary).
매 응용
- Research paper writing.
- Grant proposal.
- Conference talk.
- Tech blog (engineering science).
💻 패턴
매 LaTeX paper skeleton (NeurIPS 2026 style)
\documentclass{article}
\usepackage[final]{neurips_2026}
\usepackage{graphicx, amsmath, hyperref, cleveref}
\usepackage[capitalize, noabbrev]{cleveref}
\title{<Catchy Title: Method on Task with Number\%>}
\author{Alice Smith \\ Acme Lab \\ \texttt{alice@acme.com}}
\begin{document}
\maketitle
\begin{abstract}
We address <gap>. We propose <method>. On <benchmark>, our approach
achieves <X\%> ($\Delta$+Y\% over prior best). Code: \url{...}.
\end{abstract}
\section{Introduction}
\input{sections/intro}
\section{Method}
\input{sections/method}
\section{Experiments}
\input{sections/experiments}
\section{Related Work}
\input{sections/related}
\section{Conclusion}
\input{sections/conclusion}
\bibliographystyle{plainnat}
\bibliography{refs}
\end{document}
매 abstract template (250 words, 매 6-sentence hook)
1. [Context] <Field> has long pursued <goal>.
2. [Gap] However, existing methods <limit>.
3. [Insight] We observe that <key insight>.
4. [Method] Building on this, we propose <method>:
<2-sentence description>.
5. [Result] On <benchmark>, our method achieves <X%>,
improving over <baseline> by <Δ>.
6. [Impact] This suggests <broader implication> and
enables <downstream application>.
매 figure 1 ("teaser" — 매 abstract 의 visual)
매 좋은 figure 1 의 5 rule:
1. 매 self-contained — caption 만 읽고 message 이해 가능.
2. 매 axes labeled, units 명시.
3. 매 baseline + ours comparison (color-blind safe).
4. 매 ≤ 3 message — 매 더 많으면 split.
5. 매 vector format (PDF) — 매 raster 의 X.
매 talk pyramid (15-min conf talk)
00:00 — Hook (1 slide, 매 result tease)
01:00 — Problem (2 slides, 매 why care?)
03:00 — Insight (1 slide, 매 핵심 idea)
04:00 — Method (3-4 slides, 매 just enough)
08:00 — Results (3-4 slides, 매 main + ablation)
12:00 — Limitation (1 slide, 매 honest)
13:00 — Take-aways (1 slide, 매 3 bullets)
14:00 — Q&A
매 Twitter/X thread 의 paper drop
1/ 매 [TL;DR] — 매 1 sentence + result number + figure.
2/ Why does this matter? (매 problem framing)
3/ Insight (매 1 핵심 idea, 매 figure)
4/ How (매 architecture, 매 다이어그램)
5/ Results (매 main number, 매 baseline 대비)
6/ Limitations (매 honest)
7/ Code + paper + colab links.
매 Claude Opus 4.7 paper-review prompt (1M ctx, 매 full paper)
import anthropic
client = anthropic.Anthropic()
paper_pdf_text = open("draft.txt").read() # 매 full paper
msg = client.messages.create(
model="claude-opus-4-7",
max_tokens=8192,
system=(
"You are a senior NeurIPS reviewer. Review this paper:\n"
"1. Summary (3 sentences).\n"
"2. Strengths (3 bullets).\n"
"3. Weaknesses (3 bullets, specific section refs).\n"
"4. Questions for authors (3).\n"
"5. Score (1-10) with justification.\n"
"Be specific, cite line numbers, no generic praise."
),
messages=[{"role": "user", "content": paper_pdf_text}],
)
print(msg.content[0].text)
매 distill-style explainer (interactive, 매 React + MDX)
// 매 D3 + MDX 로 매 inline interactive figure
import { useState } from "react";
import { MathJax } from "better-react-mathjax";
export const TempScaling = () => {
const [T, setT] = useState(1.0);
return (
<div>
<p>Temperature <code>T={T.toFixed(2)}</code></p>
<input type="range" min={0.1} max={5} step={0.1}
value={T} onChange={e => setT(+e.target.value)} />
<SoftmaxPlot T={T} />
<MathJax>{`$$p_i = \\frac{e^{z_i/T}}{\\sum_j e^{z_j/T}}$$`}</MathJax>
</div>
);
};
매 결정 기준
| 상황 | Approach |
|---|---|
| 매 conference paper | IMRaD + LaTeX + arXiv preprint |
| 매 industry blog | distill-style + interactive figures |
| 매 talk (15 min) | pyramid: conclusion → method → results |
| 매 social drop | thread 7-tweet + figure 1 + code link |
| 매 grant | story arc: problem → impact → method → milestones |
기본값: paper 면 IMRaD + arXiv + 1-thread X drop + Claude Opus 4.7 self-review.
🔗 Graph
🤖 LLM 활용
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. 언제 X: 매 result fabrication. 매 method 의 invention. 매 LLM 의 "novel contribution" claim.
❌ 안티패턴
- Methods-section first sentence: 매 reader 가 not knowing 'why' 도착. 매 motivation lead.
- Equation salad: 매 prose 없이 equation 만 — 매 narrative 필요.
- Result-only abstract: 매 context 없이 number 만.
- AI-generated filler: 매 reviewer 가 매 hallmark detect.
- Buried lead: 매 main result 가 page 8 — 매 figure 1 으로.
🧪 검증 / 중복
- Verified (Mensh & Kording "Ten simple rules for structuring papers", Pinker "Sense of Style", NeurIPS guidelines).
- 신뢰도 A.
🕓 Changelog
| 날짜 | 변경 |
|---|---|
| 2026-05-08 | Phase 1 |
| 2026-05-10 | Manual cleanup — IMRaD + LaTeX + Claude Opus 4.7 review + distill |