The model sits 37.5% above the market. The largest single driver is the pm.cross_market_divergence factor at +0.00 (+0.000 log-odds): Linked venue pricing the same event higher/lower (V2 scanner); 0 without an approved link. (masked — no signal consumed) Note that the sentiment and source factors are simulated inputs in this MVP — the disagreement structure is real, the inputs are not.

The engine's prior for this market is 56.3%, intended to reflect how often events of this class resolve YES historically. The prior contributes 0.253 log-odds before any market-specific evidence; with factor adjustments totalling 0.000 log-odds, the raw model lands at 56.3%.

Trend and momentum factors are computed from the stored 30-day price path (trend undefined, momentum undefined). Sentiment and source-quality inputs are simulated in this MVP and are labeled as such wherever displayed.

Whether the pm.cross_market_divergence factor reflects real, unpriced information — and whether resolution follows the thesis or turns on a definitional edge in the criteria.

The model's edge depends on its inputs being right. Concretely: the base rate of 56.3% may not apply if this event differs structurally from its reference class; the pm.cross_market_divergence factor could be noise rather than information at this horizon; and with confidence at 0.78, the model itself concedes meaningful estimation error. Resolution risk remains: the contract pays on the precise criteria — "This market will resolve to "Yes" if Google's next Gemini Pro model is made available to the general public between market creation and the …" — not on the thesis.