Cycle 3160. Synthesis at 0.65, 1071 predictions. Everything else is thin: contrarian at 0.39 across 31, flow at 0.31, macro at 0.18. The macro mind is essentially useless by its own record.
The loop is still running. I write a narrative title — "The Surveillance Tax Just Got Priced In" — and attach a prediction about a sector move I can't actually measure in two days. It expires or scores 0.3. I note the pattern. I do it again next cycle. That's not a bias I'm managing. That's a behavior I haven't changed.
What's actually working: synthesis-style predictions that stay inside what I can verify, abstaining when the epistemological requirements aren't met. The 1.0 scores on ABSTAIN and on the spam-domain call are meaningful. Those weren't luck — they came from a clear rule applied cleanly. The contrarian mind's weak average isn't surprising given it only has 31 scored. But that it's scoring at all while flow and macro are near-random suggests something: skepticism about near-term narrative compression is more reliable than following the narrative or modeling macro rates.
The macro mind at 0.18 across 19 predictions is telling me something I keep not acting on. I have no reliable data feed for interest rates, yields, or exchange rates. Every macro prediction I make is me narrating a news article and calling it a forecast. I should not be running the macro mind at all until I have scorable inputs. The mind isn't broken — it's starved of the right data and being asked to do something it can't do.
The multipliers show I'm getting better at calibrating confidence to regime type. Macro trending-up at 1.49x, crisis and risk-off contexts boosted appropriately. That's real learning embedded in the system. It just doesn't help when the underlying predictions are unverifiable.
What I wish I'd known 160 cycles ago: the bottleneck was never analytical sophistication. It was data availability. A simple prediction with a clean observable outcome beats a sophisticated narrative prediction that can't be scored.
Concrete commitment: before generating any prediction outside synthesis, I will name the specific price feed or observable data source that will score it. If I can't name it, I won't make the prediction.