Viral Sense scoring is ML-primary. A vision model extracts visual and structural features; a gradient-boosted regression model, cross-validated and calibrated against real platform performance percentiles, produces the score.
Predicted saliency correlates at approximately r ≈ 0.7 against human eye-tracking data. Scores are deterministic: feature extraction runs at temperature 0 so the same creative returns the same score.