Calibration

What a readout is worth

Seven reads of the data at two oncology meetings in mid-2026 -- each written down and dated before the result, then scored against what actually happened. The prices here are the scorecard: proof a method kept its own score.

Before each result I write down what the data would have to show for my read to count as right, and I date it. After the result I score it -- including the rows I got wrong. This is the full card from those two meetings.

The discipline, before the method

A prediction you can quietly revise after the fact is worthless. So before each readout I locked a written, dated call -- what the data would have to show to count as a hit -- into a file I cannot edit afterward. The ASCO calls were locked May 27 and May 29; the EHA calls were frozen June 2, before any company was scored. Then the data printed, and I checked the work against it. The grades below were also run through an independent model of a different family, whose job was to catch me grading myself generously. It did, twice; these are post-correction.

The seven reads, scored

Prices are close-to-close (Yahoo Finance), bracketing each readout’s public-disclosure date.

What survives honest scoring

Read top to bottom, this is neither a winning streak nor a bust. It is a calibration record.

I show the misses because a scorecard you cannot lose on is not a scorecard. What you get is a dated, auditable read of the published data -- graded in the open against what the stock actually did, wrong rows included.

Reading the numbers honestly

These seven are the complete set I locked for these two meetings -- nothing was dropped to flatter the record. The price moves are raw close-to-close changes, not adjusted for the biotech sector’s move that week; they show that the market reacted, not how much of the reaction was company-specific. A contemporaneous move is correlation, not proof of cause. LEGN is included as context, not as a scored read -- it had no locked call; it simply illustrates the "priced before the news" pattern. Every clinical figure and price links to its primary source.

Method: pre-registration locks dated May 27 / May 29 / June 2, 2026. Clinical results from company disclosures at ASCO and EHA 2026. Prices: Yahoo Finance daily closes, close-to-close across each disclosure date. Independent adversarial review: cross-family model (DeepSeek V4), June 18, 2026.

This is how I keep score on the public reads. Point me at the one private asset you can’t afford to get wrong, and I’ll verify it against the record the same way.

or email me directly:chris@bigbio.ai

A record of how a method scored, with every finding traceable to a dated source. Full terms on the disclaimer.