TechShortsAppExperimental
V2.0.0 Baseline Established
Credibility-First (Experimental)

Credibility-First System: Baseline

From popularity metrics to probabilistic confidence and uncertainty

V2.0.0 Outcome Summary

V2.0.0 introduces the core insight: credibility should be modeled as belief under uncertainty, not popularity. The system does not attempt to measure truth directly—it estimates conservative confidence given noisy evidence.

Baseline Capabilities (V2.0.0)

Evidence Collection Baseline

The system observes implicit user behavior as noisy evidence (not truth) and stores it to update belief conservatively.

  • Watch ratio / completion as weak positive signal
  • Replays as stronger reinforcement signal
  • Bookmarks as high-intent learning signal
In V2.0.0, skips/early exits are treated as negative evidence by default (later refined in V2.0.1+).

Bayesian Belief Baseline

Each video maintains a belief state using Beta priors (default Beta(2,2)). Updates are conservative to resist early dominance and overconfidence under low data.

  • Posterior mean estimates current belief
  • Variance represents uncertainty explicitly
  • Low evidence → high uncertainty (no fake certainty)

Ranking Baseline

V2.0.0 ranks videos by credibility confidence with time decay. The system prioritizes certainty-aware ranking over engagement loops.

  • Rank uses mean × confidence (uncertainty penalty)
  • Time decay applied to prevent stale dominance
  • Cold-start remains cautious via priors

V2.0.0 Research Objectives (Baseline)

Credibility Signals Defined ✓

Established the initial mapping from user behavior signals to belief updates (positive vs negative evidence).

Uncertainty Made Explicit ✓

Confidence is not hidden. Low-evidence items remain uncertain rather than being ranked as “bad.”

Baseline System Validation ✓

Established initial consistency checks and safe defaults for missing data (priors + conservative fallbacks).

V2.0.0 Timeline

Baseline evidence model
Established
Bayesian belief state (Beta priors)
Implemented
Credibility-first ranking
Validated

Key Baseline Finding

V2.0.0 validated that credibility ranking requires explicit uncertainty and conservative belief updates. The system prefers being uncertain over becoming confidently wrong under low data.

Next steps (post V2.0.0):

  • Refine skip interpretation (skip ≠ uncredible)
  • Separate freshness from credibility (multi-feed)
  • Calibrate domain-specific decay and confidence bounds