f1000research.com 68 C
🛡️ SEO 46 🤖 GEO 79 ⚡ Perf 62 🏗️ Arch 80

f1000research.com — Global SEODiff Score 68/100

f1000research.com
📊

f1000research.com shows strong AI visibility with an ACRI of 72/100, outperforming 74% of indexed domains. In the infrastructure sector, f1000research.com outperforms the average (57), suggesting strong competitive positioning in AI search. The low ghost ratio (10%) confirms that what crawlers see matches what users see — a hallmark of strong SSR implementation. The 6.2× token bloat ratio falls within the normal range, though there is room to trim navigation, footer, and script overhead. Minimal structured data (1 block) limits the site's ability to communicate entity relationships to AI systems. Some AI crawlers are permitted while others are blocked — a mixed robots.txt policy that limits visibility in certain AI ecosystems.

68
C — Global SEODiff Score
Comprehensive search visibility assessment
Strong foundations, but Traditional SEO (46) is your bottleneck.
🎯 Top Fix: Fix title tag length → +3 pts
🔬 Automated SEODiff Assessment · Snapshot: Feb 26, 2026 · 📋 API
Does your site score higher than f1000research.com?
Run the same 40-signal audit on your own domain — free, instant results.
Scan Your Site Free →
🧮 Score Transparency — How is this calculated?
🛡️ Traditional SEO (25% weight)46 × 0.25 = 11.5
🤖 AI Readiness / GEO (40% weight)79 × 0.40 = 31.6
⚡ Performance (20% weight)62 × 0.20 = 12.4
🏗️ Architecture & Trust (15% weight)80 × 0.15 = 12.0
Weighted sum = 11.5 + 31.6 + 12.4 + 12.0
Global SEODiff Score = 68 (C)
📊 ACRI Sub-Scores (AI Readiness Detail)
80
Bot Access
avg 92
97
Rendering
avg 93
53
Structure
avg 35
42
Schema
avg 10
70
Tech Stack
avg 64
🔀
Visibility Delta: Google vs AI
Google (Tranco)
Top 6%
Rank #56184
+21 pts
Gap
AI (ACRI)
Top 26%
Score 72/100

f1000research.com punches above its weight in AI — AI visibility exceeds Google ranking. This is a competitive moat worth protecting. ACRI measures technical crawler readiness. Read the methodology →

Why f1000research.com ranks here

Tech stackHubSpot CMS
RenderingHybrid
Schema coverage1 blocks
Token bloat6.2×

Fastest improvements

  • Reduce token bloat (navigation/footer/code) so agents reach your main content faster (see Token Bloat).
  • Create an llms.txt file so AI crawlers can discover your content structure without heavy crawling. Generate llms.txt →
  • Run a full entropy audit to find which DOM regions waste the most tokens. Run Entropy Audit →
🧪

JavaScript Rendering Check

We check what AI crawlers miss when they skip JavaScript execution.

Running headless browser to simulate AI extraction…
🛡️

Traditional SEO

46/100 25 % of Global Score 🟢 High Confidence

📝 Title Tag

75 chars
Too long

Optimal range: 30–60 characters for SERP display.

📋 Meta Description

158 chars
Good length

Optimal range: 120–160 characters for snippet control.

🔤 Heading Hierarchy

  • ✗ Exactly 1 <h1> tag — found 4
  • ✓ Has <h2> headings — found 5
  • ✓ <h2> not before <h1>

🔍 Indexability

  • ✗ Canonical tag present
  • ✓ No noindex directive
  • ✓ Meta viewport set
  • ✗ HTML lang attribute
  • ✗ Hreflang tags
  • ✓ Googlebot allowed by robots.txt

🌐 Social / OpenGraph

  • ✗ og:title
  • ✗ og:description
  • ✗ og:image
  • ✗ twitter:card
📐 How the SEO Pillar score is calculated

SEO Pillar = Title (20 pts) + Meta Desc (20 pts) + Heading Hierarchy (20 pts) + Indexability (20 pts) + Social/OG (20 pts)

Each sub-score is derived from the checks above. Canonical tag, lang attribute, og:image, and a single H1 are the highest-impact items.

🤖

AI Readiness / GEO

79/100 40 % of Global Score 🟢 High Confidence

This pillar aggregates citation share, hallucination risk, bot access, schema health, and content extractability. The individual diagnostic sections below contribute to this score.

🔗

Citation Alternatives

Research
💡
Insight: In the infrastructure sector, safely.co.jp (ACRI: 90) currently has stronger AI extractability. AI models tend to prefer sources with higher semantic structure and schema coverage. Domains with ACRI < 40 see 3.5× more hallucinations. Read the research →
f1000research.com
54
Your ACRI Score
90
Industry Peer ACRI
AI models prioritize pages with strong semantic structure and schema coverage. safely.co.jp has schema coverage of 3 blocks and uses WordPress. Improve your score by implementing the remediation patches below.
📊 Side-by-Side Comparison →
🚨

Hallucination Risk

Research

Is AI lying about your brand? This panel measures how likely LLMs are to hallucinate facts when extracting information from your page.

Analyzing hallucination risk…

🤖 Bot Access Matrix

GPTBot (OpenAI)
Allowed
ClaudeBot (Anthropic)
Allowed
CCBot (Common Crawl)
Blocked
Google-Extended
Allowed
Googlebot
Allowed

👻 Rendering (Ghost Ratio) Docs

Ghost Ratio 10%
0% — Safe 50% 100% — Risk
Status Server-Side Rendered (Safe)
Rendering Type Hybrid

📊 Structure & Information Density Docs

Structure Grade 53/100 — Fair
Structured Elements 56 elements (56 lists, 0 rows, 0 headers)
Total Words667
Raw Density8.4%

🏷️ Schema Health Docs

Organization Schema ✅ Present
Product / Service Schema ⚠️ Not Found
Total Schema Blocks1 block(s) — Basic (low value for AI)

Schema Coverage Map

1/7 schema types detected
✅ Organization
❌ Product/Service
❌ Breadcrumb
❌ FAQ
❌ Article
❌ WebSite
💡Product / Service schema missing. AI models don't know this is a SaaS product. Add Product or SoftwareApplication schema so AI understands what you offer and can surface pricing/features.
💡BreadcrumbList schema missing. AI cannot understand your site hierarchy or how pages relate to each other.
💡FAQ schema missing. Adding FAQPage schema lets AI models directly extract Q&A pairs for Featured Snippets and chatbot answers.
💡WebSite schema missing. Add WebSite + SearchAction so Google can generate a Sitelinks Search Box for your brand in AI results.

📐 AI Efficiency Metrics Docs

67
AI Extractability
Medium
Crawl Cost
Low
Blocklist Risk
Extractability67/100 — AI models can partially extract answers from this page
Crawl CostMedium (40/100) — moderate for AI crawlers to process
Blocklist RiskLow — 1 of 5 AI crawlers blocked

Token Bloat Research

16%
🗑️ 84%
Useful Content (17.9 KB)Bloat (93.9 KB)
Token Bloat Ratio6.2× — Normal

Multimodal Readiness

Visual Context70% Optimized for Vision
Image Alt Coverage7 / 10 images have alt text

TDM Rights

TDM-Reservation HeaderNot set
X-Robots-Tag: noaiNot set

🔥 Structural Entropy Check Research

0 Entropy
Poor Token Bloat: High
Noise Ratio: 84.0% · SNR: 0.19 · Signal: 4583 / Noise: 24043 tokens

🔬 AI-Crawler Simulation

See your website the way AI crawlers do. CSS stripped, structure labeled, content chunked.

🌐
This is what humans see — styled, branded, visual.
Toggle to "AI Agent View" to see what GPTBot, ClaudeBot, and other AI crawlers actually extract from this page.
🤖

AI Answer Preview

NEW

See how AI models summarize your site. Left: your actual content. Right: what the LLM extracts and says about you.

Simulating AI extraction…

🔧 Tech Stack

FrameworkHubSpot CMS
AI-Readiness Score70/100
Servercloudflare
CDNcloudflare
HTTP Status200
Load Time1279 ms
Raw HTML Size111.8 KB
Visible Text Size17.9 KB

Performance & Speed

62/100 20 % of Global Score 🟢 High Confidence

⏱️ Time to First Byte

1279 ms
Slow — bots may time out or deprioritise

Google considers <200 ms "good". AI crawlers may have even shorter timeouts.

📦 Page Weight

483
DOM nodes
112 KB
HTML payload
Moderate weight — acceptable for most scenarios

🗄️ Cache & CDN

  • ✗ Cache-Control header
  • ✓ CDN cache status → DYNAMIC
  • ✓ CDN detected → cloudflare

🔬 Tracker Tax

1
tracker scripts
1
third-party domains
0.0%
token overhead
Minimal tracker load — clean signal for bots
js.hs-scripts.com
📐 How the Performance Pillar score is calculated

Perf Pillar = TTFB (35 pts) + Page Weight (25 pts) + Cache/CDN (20 pts) + Tracker Tax (20 pts)

TTFB <200 ms = full marks. DOM >3000 or payload >300 KB incurs heavy penalties. Tracker scripts beyond 5 reduce score.

🏗️

Architecture & Trust

80/100 15 % of Global Score 🟢 High Confidence

🗺️ Sitemap & Robots

  • ✓ Sitemap declared in robots.txt → https://f1000research.com/sitemap_articles.xml
  • ✓ Googlebot allowed
  • ✓ GPTBot allowed
  • ✓ ClaudeBot allowed

🔗 Linking

73
internal links
10
external links
Good internal linking — helps crawlers discover content

🔒 Security & Trust

  • ✓ HSTS header (Strict-Transport-Security)
  • ✗ Content-Security-Policy header
  • ✓ HTTP status 200 OK (got 200)

♿ Accessibility Signals

  • ✗ HTML lang attribute
  • ✓ Meta viewport for mobile
  • ✗ Single H1 for screen readers
📐 How the Architecture Pillar score is calculated

Arch Pillar = Sitemap & Robots (30 pts) + Linking (25 pts) + Security (25 pts) + Accessibility (20 pts)

Having a valid sitemap, allowing AI bots, HSTS, and a good internal link count are the highest-impact items.

🏅 AI-Verified Trust Badge

Your site scores 54/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.

AI-Verified badge for f1000research.com
Pending Audit — score below 80 threshold
<a href="https://seodiff.io/radar/domains/f1000research.com" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=f1000research.com" alt="AI-Verified by SEODiff" width="280" height="52"></a>

💡 Paste in your site footer, GitHub README, or email signature. Badge updates automatically as your score changes.

� Deep Crawl Analysis 2 pages · Deep-10

Homepage ACRI
54
Single-page score
+12
Subpages outperform homepage
Δ delta
Site-Wide ACRI
66
Avg across 2 pages · Range 51–82
Topical Cohesion
2%
Topical Drift
TF-IDF cosine similarity
Total Words
3584
Avg Bloat
34.5×
Ext. Citations
12
Page Type ACRI Token Bloat Words Status
https://f1000research.com/about
About F1000Research | How It Works | Beyond A Research Journal
pricing 82 9.4× 3238 💰 Pricing
https://f1000research.com/contact
Contact | Get In Touch | F1000Research
support 51 59.6× 346
🔗
Outbound External Citations
12 unique external domains cited across 2 pages
research4life.org ×2
google.com ×2
orcid.org ×2
fairsharing.org ×2
crossref.org ×2
twitter.com ×2
youtube.com ×2
facebook.com ×2
🔄 Re-Crawl & Update 📡 Track this Domain

Scores update automatically each month. Create a free account for on-demand re-crawls (3/month free).

🔌 API Access

Pull this data programmatically. All sub-page metrics are available via our public API.

curl https://seodiff.io/api/v1/deep10/domain/f1000research.com

Get your free API key — 100 requests/month included.

🔗 Similar infrastructure Sites

Domains with a similar tech stack, industry, and AI readiness profile to f1000research.com. Compare side-by-side.

Domain ACRI AI Score Tech Stack Token Bloat Schema
f1000research.com (this site) 54 72 HubSpot CMS 6.2× 1
easyweddings.com.au 54 75 HubSpot CMS 5.9× 1 Compare →
easyweddings.com 54 75 HubSpot CMS 5.9× 1 Compare →
songtrust.com 53 77 HubSpot CMS 6.2× 1 Compare →
3pc.de 53 73 HubSpot CMS 6.1× 1 Compare →
onsip.com 55 79 HubSpot CMS 6.6× 1 Compare →
Compare All 5 Similar Sites →
🩹

Remediation Patches

COPY-PASTE

Auto-generated code fixes tailored to f1000research.com. Copy and paste these into your codebase to improve AI visibility. These patches are mathematically proven to increase extraction accuracy →

Add WebSite + SearchAction JSON-LD
High Impact ⏱ 5 min
Enables the Sitelinks Search Box in Google and allows AI to understand your site structure.
html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "WebSite",
  "name": "F1000research",
  "url": "https://f1000research.com",
  "potentialAction": {
    "@type": "SearchAction",
    "target": "https://f1000research.com/search?q={search_term_string}",
    "query-input": "required name=search_term_string"
  }
}
</script>
Add FAQ Schema
Medium Impact ⏱ 10 min
FAQ schema lets AI models directly extract Q&A pairs. This is the easiest way to get featured in AI responses.
html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is F1000research?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add your answer here — describe what F1000research does in 1-2 sentences."
      }
    },
    {
      "@type": "Question",
      "name": "How does F1000research work?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Explain the key features and how users interact with F1000research."
      }
    }
  ]
}
</script>
📈

Projected Impact

ROI EST.

If you apply the patches above, here's the estimated improvement for f1000research.com:

Current Score
72
Projected Score
82
Improvement
+10 pts
Add WebSite schema +4 pts
Reduce token bloat +3 pts
Add FAQ schema +3 pts

*Estimates based on SEODiff's scoring model. Actual results depend on implementation quality.

📋 Data Export

Download scores and metadata for audits, client reports, or CI/CD pipelines. Exports contain computed metrics only (no copyrighted content).

All data is generated automatically and updated with each crawl. JSON exports contain scores and metadata only (no copyrighted content).

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🧭 Self-Diffing (Private Layer)

For owned domains, combine this world snapshot with private drift + regression history.
Template Drift
Track in My Site
Drift → Traffic Impact
In development coming soon
Regression Incidents
Track in My Site
Internal Linking
Deep Audit graph
Semantic Structure
GEO view in Deep Audit
Content Quality
Thin/duplicate tracking

🕒 History

Score over timeAvailable in My Site history
Drift eventsTemplate timeline + incidents
Drift → Revenue AttributionComing soon
Schema/rendering/extractability changesTracked per scan in project history