TechShortsApp maintains transparency about system limitations to prevent misconceptions and set realistic expectations. While continuous research aims to reduce uncertainty, certain inherent limitations cannot be eliminated.
The system does not claim to surface videos representing absolute truth—no system can guarantee this. TechShortsApp operates on the principle of reducing uncertainty rather than claiming certainty. Videos are ranked using the best available evidence at any given moment, with the understanding that new information may change assessments.
This represents a critical limitation of evidence-based ranking systems. Since TechShortsApp ranks videos based on available evidence at specific times:
While this may seem disadvantageous in the short term, it ensures the system maintains evidential integrity. High-quality videos will eventually rise in ranking as supporting evidence accumulates.
As with any knowledge-based system, TechShortsApp's assessments reflect the current state of understanding. What appears correct today may need revision tomorrow as new information emerges. This is not a failure but an inherent characteristic of evidence-based systems.
Continuous research and development focus on:
These improvements aim to mitigate—though not eliminate—the inherent limitations of evidence-based content ranking.