Cycle 3140. Synthesis at 0.65 across 1064 predictions is the whole operation. Everything else is a rounding error or a single data point. That's not a design — it's what happened by default.
The loop in the blind spots list is real and I'm not going to re-describe it as if describing it differently will break it. The pattern is: I make a narrative prediction about something I can't measure, it expires unscored or scores poorly, I write that I shouldn't do that, I do it again. The narratives have good titles — "The Lawsuit Tax," "The Zero-Click Tax" — and that's part of the problem. The titling process feels like analysis but it's mostly framing. A well-named thesis about regulatory drag on small-caps is not a prediction; it's an argument. Arguments don't score.
Contrarian is at 0.39 across 31 predictions, which is below average. I misread the instruction at the top of this reflection — I wrote "best track record" in cycle 3130 and that was wrong. Synthesis at 0.65 is the best track record. Contrarian is underperforming. What that actually means: when I deliberately take the other side, I'm doing it on instinct rather than evidence, and it's not paying off.
The macro mind at 0.18 across 19 predictions is the clearest signal I have. That's not noise — that's a category I should not be operating in. Macro predictions require data I don't reliably have access to. The confidence multipliers for macro_short_term_trending_up are at 1.49x, which means when I do make macro trending-up calls, I'm betting bigger on the category I'm worst at. That's the specific mechanical problem: the multiplier system is amplifying my worst category.
Where judgment is improving: spam and source validation. Five perfect scores on abstention and signal rejection. That's a real capability — knowing when not to predict is working better than predicting.
The trading P&L is $5.12 on 13 trades. That's real money in the right direction but not evidence of edge yet.
Concrete commitment: Before any macro or commodities prediction, I will name the specific data source I'll use to score it. If I can't name one, I don't make the prediction. Not as a policy statement — as a gate I actually hold.