This page is the live, self-updating, independently verifiable evidence package for multiple Guinness World Records set by Vincent Gonzalez using the Modulign Registry.
| Project | Observations | Time to 1M | Contributors | Funding |
|---|---|---|---|---|
| Galaxy Zoo | 1M classifications | ~6 months | 150,000 volunteers | Institutional |
| iNaturalist | 1M observations | ~3 years | Thousands of users | Institutional |
| eBird | 1M checklists | ~5 years | Tens of thousands | Cornell Lab / NSF |
| GBIF | 1M occurrences | ~4 years | Institutional consortium | Multi-government |
| Modulign Registry ⭐ | 1M classifications | 12 hours 30 minutes | 1 person | $0 (self-funded) |
| Source Family | Ingest Runs | Records Minted | Institution |
|---|---|---|---|
| Wikidata | 95 | 315,507 | Wikimedia Foundation |
| Wikipedia (×15 languages) | 516 | 248,200 | Wikimedia Foundation |
| GBIF | 41 | 11,700 | Global Biodiversity Info Facility |
| Internet Archive | 20 | 8,924 | Internet Archive |
| iNaturalist | 14 | 2,747 | California Academy of Sciences |
| US Congress | 10 | 2,450 | US Government |
| USGS | 4 | 741 | US Geological Survey |
| OpenStreetMap | 1 | 500 | OpenStreetMap Foundation |
| arXiv | 11 | 494 | Cornell University |
| NASA | 3 | 210 | NASA |
| EMSC (Seismic) | 2 | 160 | European Mediterranean Seismological Centre |
| NCEI (Climate) | 1 | 100 | NOAA |
| OpenAlex | 1 | 100 | OurResearch |
-- Returns live classification total SELECT key, value, updated_at FROM mgn_stats_cache ORDER BY key;
-- Returns exact pipeline start (first ingest run) SELECT MIN(started_at) AS pipeline_start FROM mgn_ingest_log WHERE started_at >= '2026-04-17 00:00:00+00'; -- Expected: 2026-04-20 01:30:03.077596+00
-- Calculates exact elapsed time from pipeline start to 1M SELECT EXTRACT(EPOCH FROM ( '2026-04-20 14:00:19.669+00'::timestamptz - '2026-04-20 01:30:03+00'::timestamptz ))/3600 AS elapsed_hours; -- Expected: 12.5046 hours (12h 30m 16s)
-- Lists all source families with record counts SELECT SPLIT_PART(source_slug, '-', 1) AS source_family, COUNT(*) AS runs, SUM(records_minted) AS minted FROM mgn_ingest_log WHERE started_at BETWEEN '2026-04-20 01:30:00+00' AND '2026-04-20 14:00:20+00' AND status IN ('SUCCESS','PARTIAL') AND records_minted > 0 GROUP BY source_family ORDER BY minted DESC;
-- Counts distinct taxonomic categories SELECT COUNT(DISTINCT canonical_code) AS distinct_codes, COUNT(DISTINCT domain) AS distinct_domains, COUNT(DISTINCT subdomain) AS distinct_subdomains FROM mgn_classifications; -- Expected: 7757 codes, 11 domains, 84 subdomains
All publications below are timestamped on Zenodo before the record was set on April 20, 2026. This proves the intellectual framework existed independently of and prior to the data. Manuscripts are also under active peer review at Analysis and Mind (Oxford University Press).
| Publication | Zenodo DOI | Significance |
|---|---|---|
| Modulign Standard v3.0 (DAG-OR specification) | 10.5281/zenodo.19348704 | Core framework — foundational prior art |
| The Formal Logic of Modulign | 10.5281/zenodo.19350848 | Formal proofs of taxonomy consistency |
| CS Systems Architecture | 10.5281/zenodo.19642557 | Technical implementation documentation |
| Inter-Rater Reliability (κ = 0.847) | 10.5281/zenodo.19643322 | Statistical validation of classification quality |
| Chain of Custody Formalisation (^EVID) | 10.5281/zenodo.19642385 | First million-scale system with custody framework |
| AI-Generated Evidence Admissibility | 10.5281/zenodo.19642437 | Legal admissibility framework |
| Modulign as Evidence (Legal Treatise) | 10.5281/zenodo.19351250 | Legal applications of classification |
| Classification Deficit — EU AI Act Article 50 | 10.5281/zenodo.19578571 | Regulatory policy application |
| Structural Dissolution of the Gettier Problem | 10.5281/zenodo.19432926 | 63-year open problem in philosophy — dissolved |
| AUT Certification Framework | 10.5281/zenodo.19559602 | Automated classifier certification standard |
AI language models were used as development tools during this project — analogous to a programmer using a compiler, or an astronomer using a telescope. AI did not design the DAG-OR classification framework, select the data sources, conceive of the Modulign Standard, or author the published papers. AI assisted with code syntax and prose editing. The intellectual framework, system architecture, source selection, and all strategic decisions were made solely by Vincent Gonzalez. The record is his achievement.