Scientific Foundation
The Gaptrium Method:
Evolution of MTTR
The peer-reviewed science behind every analysis Gaptrium™ produces.
Critical compliance notice: Gaptrium™ is not an AI tool. It operates exclusively on deterministic, traceable algorithms — not probabilistic machine learning or large language models. Every result is mathematically reproducible and auditable to the source document.
Evolutionary path
1 · Manual Framework
→
2 · MTTR Prototype
→
3 · Global Vetting
→
4 · Gaptrium™ Enterprise
Phase 1 · 2020–2021
Conceptual root &
manual validation
The core logic of the Method and Tool for Generating Table of Relevance (MTTR) was initially executed manually, validating its algorithmic performance in highly sensitive infrastructure sectors — cyber warfare and cloud governance.
Cyber Warfare Literature Synthesis · Springer / ITNG 2020
Winter, R., et al. (2020). "Cyber Mission Operations: A Literature Review." ITNG / Springer.
Cloud Provider Trust Governance · IEEE Transactions 2023
Balcão-Filho, A., Ruiz, N., et al. (2023). "Applying a Consumer-Centric Framework for Trust Assessment..." IEEE Transactions on Services Computing.
Conceptual Term Cloud — manual testing phase
Phase 2 · 2021
Formal automation &
doctoral vetting
The transition into digital automation. The method was mathematically structured alongside an early automation prototype, serving as a core pillar for doctoral defence at London Metropolitan University.
Original Prototype & Publication · ECKM 2021
Ruiz, R., et al. (2021). "Method and Tool for Generating Table of Relevance in Literature Review (MTTR)." ECKM 2021.
Doctoral Defence · London Metropolitan University 2021
Ruiz, Rodrigo de Souza (2021). "Novel approaches to applied cybersecurity..." Doctoral thesis, London Metropolitan University.
Original MTTR structural architecture — protocol, tool, and refinement loops
Engine data extraction phase
Term frequency mapping engine
Algorithmic cross-reference matrix
Phase 3 · 2024–2026
Continued academic
visibility
Following its original publication, the MTTR method has continued to appear in the academic literature on evidence synthesis automation.
Cited in · Springer Nature · Systematic Reviews 2026
Sousa, M. J., et al. (2026). "The landscape of artificial intelligence tools and platforms for evidence synthesis..." Systematic Reviews. Springer Nature.
Relevance metrics output template
Final synthesised relevance matrix table
Engineering the evolution
The open science established the proof.
Gaptrium™ built the enterprise fortress.
We evolved a rigorous academic proof of concept into a modern B2B engine — hundreds of times faster, fully integrated for legal, intelligence, and compliance ecosystems.
| Vector | MTTR | Gaptrium™ — Enterprise |
|---|---|---|
| Throughput | Manual applications or single-threaded execution | Highly automated, multi-threaded parallel processing across hundreds of documents simultaneously |
| Sovereignty | Sandbox academic testing environments | Zero data retention. Client-side local execution engineered for GDPR, UK GDPR, and Swiss nFADP compliance |
| Depth | Baseline concept parsing and relevance tabulation | Cross-silo behavioural synthesis — Gap Analysis, Heat Map, Bridge Map, Timeline, Clusters, Pulse across thousands of documents |
| Auditability | Academic peer review | Every score traceable to a specific count in a specific document. Defensible in court, regulatory review, and publication |
Scientific provenance
Gaptrium™ is inspired by the MTTR methodology — developed by the Intelligent Systems Research Centre, London Metropolitan University. Gaptrium™ shares no code, screen or implementation with MTTR. The underlying methodology was peer-reviewed and published in three institutional contexts: ITNG / Springer (2020), IEEE Transactions on Services Computing (2023), and ECKM · Coventry UK (2021). It is also cited, among hundreds of other tools and methods, in a 2026 scoping review of AI tools for evidence synthesis published in Systematic Reviews (Springer Nature). This is not proprietary opinion — it is peer-reviewed, citable science.
All publications & citations
Complete institutional
& academic record
ITNG · Springer · 2020
Winter, R., et al. (2020). "Cyber Mission Operations: A Literature Review." Information Technology: New Generations (ITNG) / Springer.
Cited in · Springer Nature · Systematic Reviews · 2026
Sousa, M. J., et al. (2026). "The landscape of artificial intelligence tools and platforms for evidence synthesis." Systematic Reviews. Springer Nature.
IEEE Transactions on Services Computing · 2023
Balcão-Filho, A., Ruiz, N., et al. (2023). "Applying a Consumer-Centric Framework for Trust Assessment of Cloud Service Providers." IEEE Transactions on Services Computing.
ECKM 2021 · Hosted by Coventry University UK
Ruiz, R., et al. (2021). "Method and Tool for Generating Table of Relevance in Literature Review (MTTR)." European Conference on Knowledge Management (ECKM) 2021.
Doctoral Thesis · London Metropolitan University · 2021
Ruiz, Rodrigo de Souza (2021). "Novel approaches to applied cybersecurity: integrating human factors and knowledge management." Doctoral thesis, London Metropolitan University.
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