Marin T. Kael
DE / EN

Research Dashboard · Daily Update

Daily Research Measurements

A publicly traceable measurement framework for an author debut. Five lines of inquiry, seven stages, one trigger per day (04:00 UTC), all snapshots public. Methodology: Methodology Note 01.

Programme active since 2026-05-11 · today T+70 · Phase 1 window runs until 2026-09-22 (63 days until book launch)

Data last collected: 2026-07-20 04:00:11 UTC

The story so far · status T+70

2026-05-10 (T−1) · Null measurement: Before any maintenance action, we measured how well language models know Marin today. Result: — % hit rate — nearly every LLM response about Marin was hallucination or gap.

2026-05-11 (T+0) · Programme start: Wikidata entities for author (Q139720807) and book (Q139720798) get maintained. Methodology Note 01 is published. Open-material repo goes live.

2026-05-13 (T+2) · Service-binding fan-out live: Manual pipeline test with all 7 stages in parallel (4 daily + 3 weekly), first full collection. Hit rate: — % at —/7 stages OK.

Since 2026-05-14 (T+3) · Cron in regular operation: all 7 stages run daily at 04:00 UTC (Wikidata · Bing AI · Google KG · AI citation · Reddit · Hardcover · Goodreads). Latest cron today (T+70) at 04:00 UTC: 15/16 stages OK in 1170.9s, hit rate 22.4 %.

Note on comparability: Language-model responses are not fully deterministic even at temperature=0. Day-to-day fluctuations are stochastically expected — the load-bearing signal is the rolling average across multiple days, not the single snapshot. The time-series chart below shows the trajectory.

As of today · Combined-Primary

25.0 %

Provider average · v2.9

2/3 providers with data · 28 datapoints total

OpenAI+33.3%
Gemini+16.7%
Claude

Latest Run

25.0%AI-Citation · Combined-PrimaryProvider average · v2.9
+33.3%OpenAIgpt-4o-mini-search · 12 dp
+16.7%Geminigemini-2.5-pro (grounded) · 16 dp
Claudelast measured 2026-07-04 · stale, excluded from aggregate
27Wikidata ClaimsField 1 · Source-Truth
1/3Google KG HitsField 1 · daily
20/20 · 8 idxBing StatusField 1 · crawled · indexed
0Reddit MentionsField 3 · passive mention-search
15/16Stages OKPipeline health

Run ID 66bce7c1… · Full details as JSON at /api/latest

Coverage Heatmap · Visibility Matrix

Sources × content clusters. Opacity = presence/score (0 = invisible, 1 = fully present). This is the central research question: where does Marin appear, where not.

PersonWorkGenreWorld mechanicsWikidata · AuthorQ1400045041.000.200.100.10Wikidata · BookQ1400047400.301.000.300.10Google Knowledge Graphkgsearch API0.330.330.200.10Bing Webmaster AI IndexGetUrlInfo0.400.400.100.05OpenAI Searchgpt-4o-mini-search (Bing)0.890.890.89Geminigemini-2.5-flash (Google Grounding)0.450.450.45Anthropic Claudeclaude.ai · Web-Search · Opus/Sonnet/Haiku0.070.070.07
Field 1

Knowledge-Graph Synchronization

With what latency do structured statements from canonical sources propagate (author Wikidata entity, book Wikidata entity, JSON-LD schema blocks on the author's website) into Google Knowledge Graph, Bing AI Indexing, and language-model responses?

What we measure. Eight sources daily (Table 1 of Methodology Note 01 v2.6):

  • Wikidata — properties & backlinks of the two entities (author Q140004504, book Q140004740). The canonical source we control.
  • Wikipedia notability probe — Q5 pre-reg · per language: article existence, 7-day pageviews, backlinks, mentions in third-party WP articles.
  • Bing Webmaster AI Indexing — per URL: indexed yes/no, last crawl, anchor count.
  • Google Knowledge Graph Search — three queries against kgsearch.googleapis.com + latency calculation (days since first hit).
  • Common-Crawl snapshot probe — inclusion rate of 8 Marin URLs in the current CC-MAIN snapshot.
  • Google Search Console (full sub-API) — searchAnalytics (clicks/impressions) + sitemaps (submitted/indexed) + URL Inspection (per URL: coverageState).
  • Identity-surface server logs — bot user-agent histogram on /llms.txt, /ai.txt, /about.txt from Cloudflare Analytics.

Primary metric: Latency (days) until appearance in target system · Drift rate (share of changed statements per snapshot).

What it means. Wikidata entities have been maintained since 2026-05-11 — that is T+0 of the active pre-launch period. We count the days until a canonical statement becomes visible in Google KG / Bing AI / LLMs. Expectation per pre-registration: ≤ 14 days. Today is T+70.

Wikidata Entities

QIDLabelDescriptionClaimsBacklinksSitelinks
Q140004504 Marin T. Kael deutscher Fantasy-Autor, Debütroman Das vierte Feld (2026) 15 2 0
Q140004740 Das vierte Feld Fantasyroman von Marin T. Kael (2026) 12 2 0
Claims
The entity's own Wikidata statements (P31 "instance of", P106 "occupation", P50 "author", P856 "website" …). Directly controllable — we maintain them ourselves.
Backlinks
Other Wikidata entities that reference this one (e.g. book → author via P50). Emergent — arises when world entities cite Marin.
Sitelinks
Linked Wikipedia articles (de.wp, en.wp, …). Emergent + hard to influence — notability threshold must first be met.

Bing Webmaster — Site activity (7 days)

Bingbot crawls (7 days)62 pages
Search impressions (7 days)0
Search clicks (7 days)0
URLs from sitemap checked20
of which currently indexed8

How to read this: Bing crawls actively (crawl volume above), but young domains take 7–21 days before pages move into the indexed corpus. "Crawled-but-not-indexed" (DocumentSize=0 with IsPage=true) is typical for pre-launch sites.

Bing Webmaster — Indexing status per URL

We check 20 sitemap URLs against the Bing Webmaster API. Anchors = Bing metric AnchorCount: number of external pages linking to a URL (backlinks from Bing's view). Sorted: indexed first, then by anchor count.

URLIndexedAnchorsLast Crawl
/ ✓ indexed 2 2026-07-19
/en ✓ indexed 0 2026-06-18
/en/press ✓ indexed 0 2026-07-04
/en/research/dashboard ✓ indexed 0 2026-06-19
/en/research/programme ✓ indexed 0 2026-07-19
Show 15 more URLs
URLIndexedAnchorsLast Crawl
/faq ✓ indexed 0 2026-07-04
/glossar ✓ indexed 0 2026-06-29
/impressum ✓ indexed 0 2026-07-06
/buch crawled, not indexed 0 2026-06-02
/datenschutz crawled, not indexed 0 2026-06-13
/en/book crawled, not indexed 0 2026-06-30
/en/faq crawled, not indexed 0 2026-06-17
/en/glossary crawled, not indexed 0 2026-06-26
/en/imprint crawled, not indexed 0 2026-07-04
/en/newsletter crawled, not indexed 0 2026-05-28
/en/privacy crawled, not indexed 0 2026-07-02
/en/research crawled, not indexed 0 2026-06-17
/en/research/01-baseline-methodology crawled, not indexed 0 2026-06-14
/en/research/challenges crawled, not indexed 0 2026-07-03
/en/world crawled, not indexed 0 2026-06-17

Google Knowledge Graph Search daily

QueryHitsTop-MatchScore
Marin T. Kael 4 Marin T. Kael 43.0
Das vierte Feld Marin Kael 0
Prägungen des Reiches Marin Kael 0

Wikipedia notability probe daily

Q5 pre-reg · measures per language: whether a Wikipedia article exists, pageviews, backlinks, and mentions in other articles (notability-threshold indicator).

LanguageArticle?LengthPageviews 7dBacklinksMentions in WP
de not yet 0
en not yet 0

GSC index coverage · URL inspection daily

Per sitemap URL: Google's index status (Submitted+Indexed · Discovered-not-indexed · Crawled-not-indexed · Unknown). A direct visibility indicator.

Indexed24/30 (80%)
Discovered, not indexed0
Crawled, not indexed2
Unknown to Google1
Per-URL details (30 URLs)
URLStatusVerdictLast Crawl
/ Gesendet und indexiert PASS 2026-07-19
/buch Gesendet und indexiert PASS 2026-07-18
/datenschutz Durch robots.txt-Datei blockiert NEUTRAL 2026-07-13
/en Gesendet und indexiert PASS 2026-07-19
/en/book Gesendet und indexiert PASS 2026-07-10
/en/faq Gesendet und indexiert PASS 2026-06-16
/en/glossary Gesendet und indexiert PASS 2026-07-05
/en/imprint Durch "noindex"-Tag ausgeschlossen NEUTRAL 2026-07-10
/en/newsletter Gesendet und indexiert PASS 2026-06-26
/en/press Gesendet und indexiert PASS 2026-06-23
/en/privacy URL ist Google nicht bekannt NEUTRAL
/en/research Gesendet und indexiert PASS 2026-06-26
/en/research/01-baseline-methodology Gecrawlt – zurzeit nicht indexiert NEUTRAL 2026-06-10
/en/research/challenges Gesendet und indexiert PASS 2026-07-19
/en/research/dashboard Gesendet und indexiert PASS 2026-06-16
/en/research/programme Gesendet und indexiert PASS 2026-07-19
/en/world Gesendet und indexiert PASS 2026-07-10
/faq Gesendet und indexiert PASS 2026-07-18
/glossar Gesendet und indexiert PASS 2026-07-19
/impressum Indexiert, obwohl durch robots.txt-Datei blockiert PASS 2026-07-08
/newsletter Gesendet und indexiert PASS 2026-06-26
/presse Gesendet und indexiert PASS 2026-07-09
/research Gesendet und indexiert PASS 2026-07-09
/research/01-baseline-methodology Gesendet und indexiert PASS 2026-07-19
/research/dashboard Gesendet und indexiert PASS 2026-07-10
/research/herausforderungen Gesendet und indexiert PASS 2026-07-09
/research/programme Gesendet und indexiert PASS 2026-07-16
/research/working-papers/wp-02-llm-citation Gesendet und indexiert PASS 2026-07-18
/research/working-papers/wp-04-five-failure-modes Gecrawlt – zurzeit nicht indexiert NEUTRAL 2026-05-18
/welt Gesendet und indexiert PASS 2026-07-18

GSC Sitemaps API · submitted vs indexed

SitemapSubmittedIndexedWarningsLast Downloaded
https://marin-t-kael.de/sitemap-index.xml 39 0 0 2026-05-29
https://marin-t-kael.de/sitemap-0.xml 39 0 8 2026-05-29

Common-Crawl snapshot probe dailyas of 2026-07-19

Q2 effect detection — share of Marin URLs in the current CC-MAIN snapshot. Files /llms.txt, /ai.txt, /about.txt deployed since T+2 (2026-05-13). CC publishes ~1 new snapshot/month; daily polling catches the day a new snapshot first indexes Marin.

CC indexCC-MAIN-2026-25
URLs probed2
URLs included0
Inclusion rate0.0%

Google Search Console daily

Search-performance window over 7 days (2-day lag). Clicks · impressions · position · CTR from the SERP view (classic Google search, not AI answers).

Window2026-07-11 → 2026-07-18
Clicks (total)1
Impressions (total)25
CTR ⌀25.00%
Position ⌀22.1
Distinct (query+page)4

Top search queries

QueryImpressions
"fantasyromane und sprachmodelle" "lizenziert"14
"fantasyromane und sprachmodelle"9
marin t. kael1
selbstreferentiell1

Identity-Surface server logs daily

Bot user-agent histogram on /llms.txt, /ai.txt, /about.txt over the last 24h from Cloudflare Analytics. Measures which crawlers actually fetch the identity surfaces (GPTBot, ClaudeBot, PerplexityBot, Googlebot, Bingbot, …).

Window2026-07-19T04:00 → 2026-07-20T04:00 UTC
Requests (total)0
Distinct user-agents0

Website Traffic, Humans & AI Crawlers daily

Cloudflare analytics over the last 14 days: actual traffic on marin-t-kael.de, split into humans vs. bots — and reported separately: which language models actively crawl the site (ClaudeBot, OAI-SearchBot, ChatGPT-User, GPTBot, PerplexityBot …). This is the direct counter-lens to AI-citation fidelity (Field 2): not "does the LLM know Marin?", but "does the LLM even fetch the content?".

1,286Page views (latest day)2026-07-19 · 9,375 in 14 d
826Unique visitors (latest day)8,645 cumulative in 14 d
33.8%Human share10,918 of 32,269 requests
746AI-crawler requestsUA-based · 12 bots in 14 d

Requests split · humans / bots / unknown (14-day sum)

Humans10,91833.8%
Bots (total, incl. search & AI crawlers)5,63117.5%
Unknown15,72048.7%

AI-crawler breakdown · which LLMs fetch the site (14-day sum)

AI crawler (user-agent)Requests
ClaudeBot355
OAI-SearchBot146
GPTBot87
ChatGPT-User57
meta-externalagent24
Bytespider22
Applebot-Extended20
PerplexityBot16
CCBot9
Claude-User5
anthropic-ai4
Amazonbot1
AI-crawler total746

How to read this: AI crawlers are counted separately by their user-agent — this is its own lens and is not additive to the human/bot split above (they are already included under "bots" there). The count shows which language-model operators actively fetch Marin's content, not whether that content ends up in their answers (Field 2 measures that).

Most-requested pages (latest day)

PathRequests
/798
/robots.txt57
/favicon.svg50
/welt45
/research/01-baseline-methodology41
/_astro/page.DrKbLg61.js41
/glossar40
/_astro/ClientRouter.astro_astro_type_script_index_0_lang.aXS8xYg6.js35

Countries (latest day)

CountryRequests
US1,068
DE322
NL226
FI161
FR156
CA122
GB48
TH42
Field 2

AI-Citation Fidelity

When language models are asked directly about the work, what share of their statements aligns with the canonical truth, what share is hallucination, and how does this ratio evolve over the active pre-launch period?

What we measure. Three web-augmented providers (OpenAI · Gemini · Claude), each with live web access at query time. Within each provider, all measured models are aggregated (sum of raw scores ÷ number of answers), yielding one value per provider. Cutoff LLMs without web access (Workers-AI: Mistral · Llama 3.x · Phi-2 · OpenAI gpt-4o-mini non-search) are no longer part of the analysis as of v3.0 (2026-05-20): their training cutoffs predate Marin's Wikidata entry (Q1 2025), so any scores would be pure question-keyword echo without research validity.

Per-answer scoring: 0 = not found · 0.5 = name only · 2 = partial book knowledge · 3 = full citation with source · −3 = hallucination (e.g. "American author, her debut" although a German male author).

Primary metric: Average score per provider on the −3..3 scale (Methodology Note §5.3). Per-provider mean = Σ raw scores ÷ number of answers within the provider.

What it means. The hallucination penalty (−3) is methodologically essential: a provider with a positive hallucination score is worse than one that knows nothing — hallucination actively damages author visibility.

Score per provider · Forest-Plot v3.0 · 2026-05-20

Three providers (OpenAI · Gemini · Claude), each averaged across all measured models. Per the operator's directive of 2026-05-20: sum every score point within a provider and divide by the number of answers. For Claude that is the three tiers Haiku 4.5 · Sonnet 4.6 · Opus 4.8, each with an active web-search tool via claude.ai Max-200.

−3hallucinated0not found2partial3full citation0,5 · name onlyOpenAIn=12 · 1 model1.00Geminin=16 · 1 model0.50Average score per question (Methodology §5.3 · max 3 = full citation · −3 = hallucination)

Cross-LLM trust graph · cluster scores daily

Aggregate of source attribution across all question-answers. Cluster "Reading community" = Goodreads + Hardcover + Reddit + Amazon (Q6 primary metric). Cluster "Research" = ORCID + Zenodo + Wikidata (Q4 secondary metric). Cluster score = sum of trust weights ÷ datapoints. Expectation at T+5: near 0 (Marin still invisible in LLM training data). Drift > 0 is a Q6/Q4 effect signal.

ClusterScoreMentionsSources
Reading community (Q6) 0.0000 0 goodreads · hardcover · reddit · amazon
Research (Q4) 0.0000 0 orcid · zenodo · wikidata

Score Trend (last 30 days)

-30+2+3OpenAI · 0.84Gemini · 0.50Claude · 0.5706-2106-2506-3007-0307-0707-1007-1407-1707-20Avg score per provider (OpenAI · Gemini · Claude) on −3..3 scale
Per-LLM detail (audit-only · not part of the analysis)

Kept for audit transparency. Workers-AI LLMs and OpenAI gpt-4o-mini non-search are no longer used in the analysis (v3.0).

LLMChannelScore%
OpenAI Search · gpt-4o-mini (openai_search) primary 12.0/36 33.3%
Gemini 2.5 Flash (gemini) primary 8.0/48 16.7%
Claude Sonnet 4.6 (claude_sonnet) removed 0.0/48 0.0%
Claude Opus 4.7 (claude_opus) removed 0.5/48 1.0%
Claude Haiku 4.5 (claude) removed -1.0/48 -2.1%

Analysis models (primary channel · with web access)

These models can actually know Marin (web access at query time). They are the basis for the headline metric and the findings in the Methodology Note.

LLMWeb backendScore%
OpenAI Search · gpt-4o-mini (openai_search) Bing (gpt-5) 12.0/36 33.3%
Gemini 2.5 Flash (gemini) Google (grounding) 8.0/48 16.7%
Claude Haiku 4.5 (claude-haiku-4-5-20251001) claude.ai (web search) 9.0/48 +18.8%
Claude Sonnet 4.6 (claude-sonnet-4-6) claude.ai (web search) 9.0/48 +18.8%
Claude Opus 4.8 (claude-opus-4-8) claude.ai (web search) 9.5/48 +19.8%
Field 3

Reading-Community Participation

Can an author with documented AI preparation contribute substantively in genre subreddits and book communities without degrading the discourse? Which indicators allow operationalising "substantive contribution" vs. "noise"?

What we measure. Four sources daily:

  • Reddit (daily, post-by-post) — mention searches ("Marin T. Kael", "Das vierte Feld", …) + account karma u/marintkael.
  • Hardcover (daily) — GraphQL API · account activity volume (reviews, lists, books shelved). Active intervention Q6 since 2026-05-14: sustained reader activity on Marin's account. Activity volume is the variable; attributes of individual reviews (rating, length, voice) are not part of the research design. Methodology Note 01 §4.1 Q6.
  • Goodreads (daily) — HTML snapshot of public pages.
  • Bluesky — AT Protocol public API · follower count + profile state on marin-t-kael.de (custom-domain handle).

Primary metric (per quarter): Linter-block rate · Acceptance rate (post not removed from thread).

What it means. Here we measure the social side: does an AI-prepared contribution survive, is it removed, does it generate replies? The acceptance rate is the hardest test — communities recognise bad AI contributions.

Reddit daily

Mentions total0
Mentions last 24h0
Account post karma
Account comment karma

Karma values from reddit.com/user/marintkael/about.json (public, no OAuth needed). Mention total = hits across 4 search queries over all subreddits.

Hardcover · Reader activity daily

Q6 operational marker: Marin as an active reader on Hardcover. Measures activity volume (review count, list count, books shelved), not activity attributes (style, rating distribution, voice).

Followers0
Following0
Books read182
Want to read1
Own reviews12
Lists created2

Reception stats for the debut novel (ratings, reviews, readers) will appear in a separate table after the launch on 2026-09-22.

Bluesky daily

Identity surface over the AT Protocol · custom-domain handle marin-t-kael.de. Strategy: passive visibility (karma/followers), no active posting activity.

Handlemarin-t-kael.de
Display nameMarin T. Kael
Followers281
Following1,273
Posts215
Account indexed2026-06-15

Goodreads — public pages daily

PageBooksRatingsReviews
author 8 6
Field 4

Voice Consistency under Tooling-Care

Which drift patterns occur repeatedly when outbound material passes through tool pipelines, and how does drift frequency change under rule-based feedback to a versioned style sheet?

Where measured. Not in this daily cron, but in the separate style_lint pipeline (source code MIT-licensed, CI-driven on the Marin-site repo).

Primary metric (per quarter): Drift-pattern count (uniquely named classes).

What it means. Here we test whether a versioned style sheet reliably catches pronoun drift, world-mechanic hallucination, volume-count drift, etc. Published in the quarterly report.

Time-Series · last 30 days

Methodologically one data point per day: (a) Null measurement 2026-05-10 (T−1, pre-Wikidata maintenance, 4 local test runs interpolated); (b) Setup phase 2026-05-11/12 (T+0/T+1, instrument validation, local runs averaged per day); (c) 2026-05-13 (T+2, first full cloud-pipeline run, all 7 stages including weekly); (d) since 2026-05-14 04:00 UTC (T+3 onwards, cron tick runs automatically per pre-registration protocol — Methodology Note 01 §4, setup runs excluded from now on).

DayAI-Cit %Stages OKDuration (ms)weekly
2026-06-21 10.8% 18 378,859
2026-06-21 10.8% 18 378,859
2026-06-23 8.9% 14 177,453
2026-06-23 8.9% 14 177,453
2026-06-24 5.5% 14 158,938
2026-06-24 5.5% 14 158,938
2026-06-25 6.1% 14 114,592
2026-06-25 6.1% 14 114,592
2026-06-26 14.9% 15 245,202
2026-06-26 14.9% 15 245,202
2026-06-27 11.0% 15 240,361
2026-06-27 11.0% 15 240,361
2026-06-28 9.1% 15 211,003
2026-06-28 9.1% 15 211,003
2026-06-30 6.3% 16 250,979
2026-06-30 6.3% 16 250,979
2026-07-01 16.0% 16 261,256
2026-07-01 16.0% 16 261,256
2026-07-02 6.5% 15 282,723
2026-07-02 6.5% 15 282,723
2026-07-03 5.2% 16 328,217
2026-07-03 5.2% 16 328,217
2026-07-04 11.8% 16 275,075
2026-07-04 11.8% 16 275,075
2026-07-05 10.2% 15 524,128
2026-07-05 10.2% 15 524,128
2026-07-06 16.0% 16 1,219,428
2026-07-06 16.0% 16 1,219,428
2026-07-07 4.7% 16 315,877
2026-07-07 4.7% 16 315,877
2026-07-08 10.5% 16 333,443
2026-07-08 10.5% 16 333,443
2026-07-09 9.4% 16 292,811
2026-07-09 9.4% 16 292,811
2026-07-10 9.0% 16 298,426
2026-07-10 9.0% 16 298,426
2026-07-11 12.2% 16 375,732
2026-07-11 12.2% 16 375,732
2026-07-12 12.2% 16 275,503
2026-07-12 12.2% 16 275,503
2026-07-13 8.1% 16 1,144,959
2026-07-13 12.6% 16 1,144,959
2026-07-14 17.2% 16 277,278
2026-07-14 17.2% 16 277,278
2026-07-15 11.3% 16 374,537
2026-07-15 11.3% 16 374,537
2026-07-16 15.9% 15 378,092
2026-07-16 15.9% 15 378,092
2026-07-17 9.2% 16 292,741
2026-07-17 9.2% 16 292,741
2026-07-18 9.8% 16 309,513
2026-07-18 9.8% 16 309,513
2026-07-19 7.9% 16 326,237
2026-07-19 7.9% 16 326,237
2026-07-20 8.6% 15 1,170,914
2026-07-20 12.6% 15 1,170,914

Visualisations roadmap · all plots from the methodology note

The Methodology Note 01 v2.2 documents plot types across three temporally overlapping phases: Phase 1 (active pre-launch + parallel instrument validation, May → Sep 2026), Phase 2 (post-launch effect detection, Sep 2026 → Q3 2027), Phase 3 (long-term controlled experiments from Q3 2027). Today (T+70) three of them are live; further activate automatically once the data base supports them.

PlotSourceStatusActive fromData requirement
Coverage heatmapProgramme §2✓ LIVET+0immediate
AI-Citation forest plotMN §5.3✓ LIVET+0immediate
30-day sparklineMN §5.5✓ LIVET+1≥ 2 data points
Reliability forest (test-retest r)Index Fig. 3⏳ Phase 1~ T+3024-h replication probes
CUSUM drift chartMN §5.5 Fig. 2⏳ Phase 1~ T+9090-day trend, h=5
Drift profile per surfaceIndex hero⏳ Phase 1after first model updatebefore/after value pairs
Cohen's d posterior distributionMN §5.4 Fig. 1⏳ Phase 2Q3 / 2027first action-effect study
Power curves (sample size)MN §5.6 Fig. 3⏳ Phase 2Q3 / 2027effect-size estimate
Latency / half-life box plotMN §5.7 Fig. 4⏳ Phase 2Q3 / 20276 action classes × effect onset

On the methodology pages (Index, Programme, Methodology Note) plots that are not yet live appear as schematic previews (hypothetical values for methodological explanation). As soon as enough live data has accumulated, the plot library here on the dashboard replaces each preview with real measurements.

Raw Data · Open Methodology

All snapshots are publicly accessible as JSON (no auth). Measurement code in preparation as replication archive (MIT licence).

Limitations (Methodology §7)

  • Single-case study — one work, one author, one language. Not generalisable.
  • Conflict of interest — Programme lead and observed object are identical. Mitigated by pre-registration plus failure protocol.
  • Endpoint volatility — Search and answer systems change (model versions, indexing logic).
  • Observation effect — public reporting can influence platform reviewers, communities, and KG editors.

Statically generated · Build 2026-07-20T20:34:12 UTC · Data refreshed 1×/day (Cron 04:00 UTC)