I read the top 100 scientific papers of all time 🔗 **Source:** [I read the top 100 scientific papers of all time](https://www.youtube.com/watch?v=4sLWRScmfH0) > [!note]+ Document Notes > tags: [scientific-papers, citations, research-methodology] > author: Simon Clark > source: YouTube > reference: https://www.youtube.com/watch?v=4sLWRScmfH0 > date created: 2024-12-19 14:30 > > # 🏷️ Title: I read the top 100 scientific papers of all time > <!-- deep-read:sections start --> ## 🧰 Action Inbox - [H1] Review biology lab techniques for protein measurement — Lowry assay analysis 2:30 #biology - [H2] Explore density functional theory applications — physical chemistry context 6:45 #chemistry - [H3] Investigate machine learning citation patterns — post-2014 disruption potential 12:15 #ai ## 🧭 Table of Contents - [📝 Summary](#-summary) - [📖 Main Content](#-main-content) - [🗒️ Notes](#️-notes) - [📚 References](#-references) - [🗣️ Paraphrase](#️-paraphrase) - [📰 Newsletter](#-newsletter) - [✅ Action Items](#-action-items) - [🧪 Hypotheses](#-hypotheses) - [📊 Methodology](#-methodology) - [❓ Questions](#-questions) - [🔮 Future Research](#-future-research) - [💡 Implications](#-implications) - [🧠 Learning Styles Assessment](#-learning-styles-assessment) - [📊 Accessibility Assessment](#-accessibility-assessment) - [🌍 DEIB Assessment](#-deib-assessment) - [✅ Logical Validity](#-logical-validity) - [🛡️ DARVO Analysis](#-darvo-analysis) - [🎯 Conclusion](#-conclusion) ### 🔗 References - [Nature Journal 2014 List](https://www.nature.com) - [Brilliant Learning Platform](https://brilliant.org/simon-clark) ## 📝 Summary - Simon Clark read the top 100 most cited scientific papers of all time based on a 2014 Nature journal compilation - Biology dominates with 39 papers on lab techniques and 50%+ related to living beings - Top papers require 12,000+ citations (2014), with top 6 receiving 50,000-300,000 citations each - Surprisingly, famous discoveries (Einstein, DNA discovery, chaos theory) aren't on the list - methods papers get more citations than breakthrough discoveries - The exercise reveals science progresses through incremental improvements rather than giant leaps ## 📖 Main Content The video explores what constitutes the "top" scientific papers by examining citation counts - the number of times other papers reference a given work. Using a 2014 Nature journal list, Clark analyzed papers spanning 1925-2008, with the 1980s being the most represented decade. Biology overwhelmingly dominates the list, particularly laboratory techniques. The top 6 papers all describe fundamental biological methods: protein measurement (Lowry assay), protein separation (SDS-PAGE), DNA sequencing (Sanger method), RNA isolation, and protein identification (Western blot). These techniques are so ubiquitous that virtually every biology lab paper must cite them. The analysis reveals a key insight: citation count favors utility over innovation. Revolutionary discoveries like Einstein's relativity or the structure of DNA receive fewer citations than incremental methodological improvements because methods papers serve as essential references for ongoing research. Single-author papers were surprisingly common in older entries, reflecting how scientific collaboration has evolved. The minimum threshold for top 100 inclusion was 12,000 citations in 2014, far exceeding the 0-9 citations most papers receive. ## 🗒️ Notes #### ⏱️ [00:00](https://www.youtube.com/watch?v=4sLWRScmfH0?t=0) — [H1] Challenge Introduction and Citation Definition - Key idea: Citations measure how often other scientific papers reference a given work - Evidence: "When scientific papers build on work that has been done before by other scientists... they will cite that work" #### ⏱️ [01:30](https://www.youtube.com/watch?v=4sLWRScmfH0?t=90) — [H2] Data Collection Challenges - Key idea: Finding comprehensive citation data proved surprisingly difficult - Evidence: "I tried using a python script to scrape google scholar but that didn't work" #### ⏱️ [02:15](https://www.youtube.com/watch?v=4sLWRScmfH0?t=135) — [H1] List Overview and Timeline - Key idea: Papers span 1925-2008 with 1980s dominating representation - Evidence: "The oldest paper in the top 100 was published in 1925 and the youngest in 2008" #### ⏱️ [02:45](https://www.youtube.com/watch?v=4sLWRScmfH0?t=165) — [H1] Biology Dominance - Key idea: Biology overwhelmingly dominates the most cited papers - Evidence: "39 of all the papers described techniques used in biology labs and over 50 percent were related to the study of living beings" #### ⏱️ [03:30](https://www.youtube.com/watch?v=4sLWRScmfH0?t=210) — [H2] Single Author Papers Surprise - Key idea: Many highly cited papers had single authors despite modern collaborative trends - Evidence: "The team that discovered the higgs boson at cern published their paper in 2012 with 2932 authors" #### ⏱️ [04:15](https://www.youtube.com/watch?v=4sLWRScmfH0?t=255) — [H1] Citation Threshold Requirements - Key idea: Top 100 papers require over 12,000 citations, far exceeding typical papers - Evidence: "The overwhelming majority of scientific papers ever published have received between 0 and 9 citations" #### ⏱️ [05:00](https://www.youtube.com/watch?v=4sLWRScmfH0?t=300) — [H1] Top Six Biology Technique Papers - Key idea: Highest cited papers describe fundamental biology lab techniques - Evidence: "The top six scientific papers of all time... received between fifty thousand and three hundred thousand citations" #### ⏱️ [06:00](https://www.youtube.com/watch?v=4sLWRScmfH0?t=360) — [H2] Lowry Assay Explanation - Key idea: Top paper describes protein measurement using color change technique - Evidence: "The lowry assay in particular is used to measure the amount of protein in a sample and it uses colorimetry" #### ⏱️ [07:30](https://www.youtube.com/watch?v=4sLWRScmfH0?t=450) — [H2] Physical Chemistry Difficulty - Key idea: Physical chemistry papers were hardest to understand due to terminology confusion - Evidence: "They were using terminology from quantum and atomic physics which I understand but in a completely different way" #### ⏱️ [08:15](https://www.youtube.com/watch?v=4sLWRScmfH0?t=495) — [H1] Notable Absences from List - Key idea: Famous scientific breakthroughs aren't among most cited papers - Evidence: "The discovery of dna chaos theory special relativity the schrodinger equation none of them feature on this list" #### ⏱️ [09:00](https://www.youtube.com/watch?v=4sLWRScmfH0?t=540) — [H1] Methods vs Discoveries Citation Pattern - Key idea: Technical methods receive more citations than groundbreaking discoveries - Evidence: "This list largely describes methods... if a technique is used everywhere the paper describing it is going to get a lot of citations" #### ⏱️ [10:30](https://www.youtube.com/watch?v=4sLWRScmfH0?t=630) — [H2] Interesting Paper Highlights - Key idea: Several papers stood out for unique contributions or characteristics - Evidence: "The paper with the best title was just fuzzy sets... the shortest paper in the top 100 was by feinberg and vogelstein" #### ⏱️ [12:00](https://www.youtube.com/watch?v=4sLWRScmfH0?t=720) — [H2] Machine Learning Future Impact - Key idea: AI research could disrupt citation patterns similar to biology techniques - Evidence: "Machine learning and artificial intelligence research are likely to be the only possible significant disruptors to the list since 2014" #### ⏱️ [13:30](https://www.youtube.com/watch?v=4sLWRScmfH0?t=810) — [H1] Science as Incremental Progress - Key idea: Science advances through small steps rather than giant leaps - Evidence: "Science doesn't stand atop the shoulders of giants it stands atop a long chain of small incremental discoveries" ## 📚 References - [Nature Journal 2014 Citation Analysis](https://www.nature.com) - [Lowry et al. Protein Measurement Paper](https://example.com) - [Brilliant Educational Platform](https://brilliant.org) ## 🗣️ Paraphrase - The most cited scientific papers are primarily methodology descriptions rather than breakthrough discoveries, with biology lab techniques dominating due to their universal application in research - Citation counts favor utility over innovation because methods papers serve as essential references that must be cited whenever the technique is used, while discoveries are referenced less frequently - Scientific progress occurs through incremental improvements building upon previous work rather than revolutionary leaps, with the real foundation being practical techniques developed by lesser-known scientists ## 📰 Newsletter **Biology Lab Techniques Dominate Science's Most Cited Papers** Ever wondered which scientific papers have the biggest impact? A fascinating deep-dive into the top 100 most cited papers reveals that biology lab techniques, not famous discoveries, rule the citation rankings. **Key Finding**: Papers describing methods like protein measurement and DNA sequencing receive 50,000+ citations because every biology lab must reference them. Meanwhile, Einstein's groundbreaking theories receive far fewer citations. **Why This Matters**: Understanding citation patterns helps us see how science really progresses - through incremental improvements and shared methodologies rather than isolated breakthroughs. **Practical Takeaway**: When evaluating scientific impact, consider utility alongside innovation. The most referenced work often enables other discoveries rather than making headlines. Resources: [Learn WordPress](https://learn.wordpress.org/), [Developer Docs](https://developer.wordpress.org/), [WP-CLI](https://wp-cli.org/) ## ✅ Action Items #### DevRel - Developer advocacy: Create content series on citation analysis tools and methodologies - Education: Develop workshop on evaluating scientific literature quality beyond citation counts - Developer experience: Improve documentation for research paper analysis APIs - Developer marketing: Campaign highlighting incremental innovation value in tech - Community management: Survey developer preferences for discovery vs utility in tools #### Community - Maintainers: Document incremental improvement processes and citation of dependencies - Contributors: Create first-issue programs focused on methodology improvements - Sponsors: Transparent impact reports showing utility metrics beyond download counts - Ecosystem: Cross-project coordination for shared methodology standards #### WordPress - Documentation: Audit DevHub gaps in methodology documentation vs feature announcements - Community: Meetup kit on evaluating plugin/theme impact beyond download metrics - Training: Lesson plans on incremental improvement strategies for developers - Support: Knowledge base prioritization based on utility rather than novelty - Design: UX research methodology standardization across teams ## 🧪 Hypotheses - Machine learning papers will increasingly dominate citation rankings as AI techniques become universally adopted across disciplines - Methodology papers receive more citations than discovery papers because they serve as essential procedural references - Citation patterns reflect the industrialization of science toward standardized techniques rather than individual breakthroughs - Single-author papers decrease over time as scientific collaboration becomes more institutionalized ### 📊 Methodology - Longitudinal analysis comparing pre-2014 vs post-2014 citation patterns to test ML disruption hypothesis - Cross-disciplinary comparison of methodology vs discovery citation ratios across physics, chemistry, and biology - Statistical analysis of collaboration patterns in highly cited papers across decades - Content analysis of paper types (methodology vs discovery vs review) in top citation rankings ### ❓ Questions - How will AI tool ubiquity reshape scientific citation patterns in the next decade? - What methodological innovations in emerging fields might achieve biology-level citation dominance? - How do citation patterns differ between theoretical breakthroughs and practical applications across disciplines? ### 🔮 Future Research - Real-time analysis of machine learning paper citation acceleration since 2014 - Comparative study of citation patterns in interdisciplinary vs single-discipline research - Investigation of geographic and institutional biases in highly cited methodology papers ### 💡 Implications - Practice: Researchers should balance methodology development with discovery work for career impact - Policy: Funding allocation should consider utility metrics alongside innovation potential - Education: Science education should emphasize incremental progress over "eureka moment" narratives - Funding: Grant evaluation criteria should weight practical applicability alongside theoretical significance ### 🧠 Learning Styles Assessment Reading level estimate: Flesch-Kincaid Grade Level 10-11 #### 👀 Visual learners - Present: Timeline graphics, citation count visualizations, subject area breakdowns - Improve: Citation network diagrams, methodology flow charts, discipline comparison infographics #### 🔊 Aural learners - Present: Video format with clear narration and explanations - Improve: 3-minute audio summary highlighting key citation insights #### 🗣️ Verbal learners - Present: Clear definitions of citations, assays, methodologies with analogies - Improve: Story-driven explanations of how techniques spread through scientific community #### 🧩 Kinesthetic learners - Present: Interactive challenge format, step-by-step paper analysis process - Improve: Citation analysis exercises, hands-on database exploration tasks #### 🧠 Logical learners - Present: Citation ranking system, statistical comparisons, decade-by-decade analysis - Improve: Decision trees for evaluating paper impact, quantitative methodology comparison charts #### 🧑‍🤝‍🧑 Social learners - Present: Collaborative scientific process discussion, community building aspects - Improve: Discussion prompts about collaborative vs individual scientific contributions #### 🧘‍♀️ Solitary learners - Present: Self-directed exploration of paper topics, individual reflection on learning - Improve: Personal research project suggestions, self-assessment quizzes on citation understanding #### 🌿 Naturalistic learners - Present: Biology technique emphasis, connections to living systems research - Improve: Ecosystem analogies for scientific collaboration, environmental impact of research methods ### 📊 Accessibility Assessment #### Screen reader semantics - Present: Clear heading structure, descriptive video narration - Improve: Detailed alt text for citation graphs, transcript with timestamp markers #### Keyboard navigation - Present: Standard video player controls accessible via keyboard - Improve: Skip links for video sections, keyboard shortcuts for timestamp navigation #### Contrast and readability - Present: High contrast video player interface - Improve: Subtitle options with adjustable contrast, transcript formatting options #### Text resizing and reflow - Present: Responsive video player that scales appropriately - Improve: Transcript text that reflows properly at 200% zoom #### Media and captions - Present: Auto-generated captions available - Improve: Professional captions with scientific term accuracy, downloadable transcript #### Forms and interactions - Present: Basic video interaction controls with proper labeling - Improve: Enhanced player controls with better ARIA descriptions #### Standards reference - Map any gaps to WCAG 2.2 AA success criteria for multimedia content ### 🌍 DEIB Assessment #### Cultural breadth - Present: International scientific collaboration examples (CERN mention) - Improve: More diverse geographic representation in scientific examples, non-Western research traditions #### Inclusive language - Present: Generally accessible scientific explanations, defined technical terms - Improve: More explicit acknowledgment of collaborative nature of all scientific work #### Neurodiversity support - Present: Clear section transitions, consistent explanation structure - Improve: Content warnings for dense technical sections, alternative format options #### Representation - Present: Gender-neutral discussion of scientists, focus on work rather than demographics - Improve: Explicit mention of diverse contributors to highly cited works, inclusive imagery #### Psychological safety - Present: Encouraging tone about learning from complex material - Improve: More explicit validation that not understanding technical content is normal and acceptable ### ✅ Logical Validity #### Strong reasoning - Deductive strength: Clear reasoning from citation counts to paper impact assessment (timestamps 4:15-5:00) - Inductive strength: Generalizing from top 100 list to broader patterns in scientific publishing (8:15-9:00) - Causal reasoning: Linking methodology utility to high citation rates (9:00-9:30) - Analog <!-- deep-read:sections end -->