Technical Report 3: Cognitive Architectural Benchmarking Under Severe Information Fragmentation — Meta-Pipeline Routing Engine for Context-Aware Hybrid Orchestration
Year: 2026
Type: report
Abstract: Third of three independent technical reports presenting the scientific validation of the MEQATEC® framework through the Adaptive Environmental Monitoring System (AEMS). This report presents a cross-framework comparative analysis integrating results from Reports 1 and 2, proposing a novel Meta-Pipeline Routing Engine architecture for context-aware hybrid orchestration between AEMS and MEQATEC® reconstruction strategies. Experimental conditions:- Dataset: High-frequency hydrographic time series from Puyuhuapi Fjord, Chilean Patagonia- Target variable: Surface water temperature (temp)- Sample size: N=119 quality-controlled observations (post-QC)- Missing data scenarios: 20%, 30%, and 40% under MCAR assumption- Comparative frameworks: AEMS (5 baseline models) vs MEQATEC® (mix_imputed engine) Key findings:- AEMS excels in low-to-moderate missingness (≤25%) where local temporal continuity provides strong predictive signal- MEQATEC® demonstrates superior resilience under extreme fragmentation (>25%)- Computational complexity analysis: MEQATEC® scales as O(n log n), suitable for edge deployment- Proposal for context-aware Meta-Pipeline Routing Engine that dynamically switches between frameworks based on real-time missingness ratio Architectural proposal:- Routing threshold: M_ω ≤ 25% → AEMS (Random Forest / Spline)- Routing threshold: M_ω > 25% → MEQATEC® (mix_imputed)- MEQATEC® positioned as fail-safe mechanism for catastrophic sensor failures Strategic implications:- Balanced approach for Digital Public Infrastructure deployments- Applicable to satellite-geospatial data acquisition platforms- Suitable for collaborative international marine research networks This report is formally referenced in Quezada, M. (2026) "MEQATEC®: A Modular Framework for Environmental Data Engineering" Technical Preprint v2.1.
Author: Soares de Souza, Celio
Institution: Universidade Estadual Paulista (Unesp)
Language: English
Subfield: Geology
Field: Earth and Planetary Sciences
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7166190860