All recordings

Recorded run

Blank start, first rubric after 21 stories

Same setup as the first recording, but the first rubric is proposed after 6 label transitions instead of 20. The loop writes its first rubric at story 21 and gets about 13 optimizer calls instead of 4.

What to notice

  • The cyclotron scored 77.1%, 94.3%, 92.9%, 95.7% across the 4 windows of 70 stories.
  • Rejecting everything would have scored 84.3%, 80.0%, 78.6%, 84.3%. Read each accuracy beside that number.
  • In the last window the cyclotron beat that baseline by 11.4 points.
  • The first rubric proposal arrived at cycle 21. Until then the decision model worked from the blank start.
  • In the last window the decision model alone scored 94.3%, so the cyclotron's added work helped there.
  • The first window is much higher because the first rubric arrives about 60 stories sooner.
  • The later windows end in the same range as the default trigger, at the cost of more optimizer calls.

Setup

Full setup of Blank start, first rubric after 21 stories
Decision modelJev 1.13.0 (jev)
LLM optimizergpt-6-luna
ObjectiveAccuracy
Starting rubricBlank (no written rubric)
Stories reviewedEvery story
Rubric changes consideredEvery 6 cycles
Idea screeningOff
Max rubric optimizationsnull
Rubric trigger basislabel_transitions
Selection policy{"aggregation":"positive","max_secondary_regression":0,"minimum_secondary":null,"positive_class":null,"primary":"accuracy","secondary":null}
First rubricCycle 21
Corpuseditorial-relabel-v3-1, 287 stories
Window size70 stories
Recorded2026-10-11
Engine commitc060abd

Accuracy by window

Each window is 70 stories. The last column is what rejecting everything would have scored.

Accuracy by window of 70 stories
WindowCyclotronDecision model aloneRejecting everything
Stories 1–7077.1%71.4%84.3%
Stories 71–14094.3%92.9%80.0%
Stories 141–21092.9%92.9%78.6%
Stories 211–28095.7%94.3%84.3%
0%25%50%75%100%70140210280stories, to the end of each window
CyclotronDecision model aloneRejecting everything

How the answers were wrong

Accuracy says how often an answer was wrong. These tables say which way. They count the 280 stories whose right answer was revealed.

Final decision
PublishedRejected
Should be published51 stories3976.5% of those to publishPublished: right1223.5% of those to publishRejected: wrong
Should be rejected229 stories167.0% of those to rejectPublished: wrong21393.0% of those to rejectRejected: right
Each row is the answer we should have given. Heavy borders and bold numbers mark right answers. Of the stories it published, 70.9% were right. Of the stories to publish, it found 76.5%.
Decision model alone
PublishedRejected
Should be published51 stories4588.2% of those to publishPublished: right611.8% of those to publishRejected: wrong
Should be rejected229 stories2812.2% of those to rejectPublished: wrong20187.8% of those to rejectRejected: right
Each row is the answer we should have given. Heavy borders and bold numbers mark right answers. Of the stories it published, 61.6% were right. Of the stories to publish, it found 88.2%.

Of 51 stories that should be published, the final decision found 39 and the decision model alone found 45. Of 229 stories that should be rejected, the final decision published 16 and the decision model alone published 28.

Cost

About $0.25 in model calls at list prices: 2,313 decision-model calls ($0.15) and 13 optimizer requests ($0.10).

Price basis: list prices, USD per million tokens, applied to the provider-reported usage on every recorded call; decision model jev (TypeSafe's published price); optimizer gpt-6-luna (LiteLLM model price table (standard tier), read 2026-10-11).

Where the labels came from

Labels are simulated. Original labels came from a single labeling model run under a written rubric; an offline audit found it over-published against that rubric. These v3 labels come from two independent blind relabeling passes under an explicit written policy; only stories where both passes agreed are included.

Replay the run

One correction can improve the next tested decision.

Cycle 280 of 280 · 280 revealed · recorded agreement

cyclotron looprubricexamplesitemdecision modelsupporting questionsML modelPublish86%decisionreviewerreviewed labeltrainscombines classifier signals

A standalone model repeats its answer. cyclotron records the correction, tests guidance and configuration changes, then uses only accepted evidence to align later decisions.

This recorded decision

SpaceX successfully launches its first crewed spaceflight

Model: publish · 82%

Reviewer: publish

SpaceX launched NASA astronauts Hurley and Behnken on Crew Dragon, the first private company to send astronauts to orbit and the first US crewed launch since the shuttle.

Recorded feedback policy: All. Realized feedback is shown in the playback.

Recorded editorial run · Run

Cycle 280 of 280
Training label
Cycle
Model decision
Human label
Optimization
Evaluation

Prediction, before the label

publish · 82% confidence

Reviewer label

publish · prediction matched

What the revealed feedback says so far

Recall
77%
Of the items that should be a yes, how many it found.
30 of 39 · 95% interval 62%–87%
Precision
94%
Of the items it said yes to, how many were right.
30 of 32 flagged
Accuracy
95%
Of all items, how many it got right.
189 of 200; always “reject” would score 81%

Accuracy is the share of decisions that matched revealed labels. Precision asks how often a “publish” call was right; recall asks how many actual “publish” stories were found. These are running totals, not future results.

Simulated reviewer replay

Visual replay only — clicking these controls never changes the recorded run.

Editorial decision

Recorded agreement

Recorded simulated reviewer explanation, replayed after the prediction. Ground-truth source evidence remains separate from optimizer feedback. The run records 280 explanations; the last optimizer proposal came at cycle 269, and the explanations after it were recorded but followed by no optimizer request. Only recorded correction events appear below.

Curated public source

SpaceX successfully launches its first crewed spaceflight

Wikinews reports: SpaceX successfully launches its first crewed spaceflight. The original linked article provides the complete reporting context.

Brief adapted and shortened for this demo; see the original Wikinews article for the complete work. Read original · CC BY 2.5 (Wikinews policy; articles dated through 2024-12-15).

What happened after the label

No optimization was due. cyclotron recorded the prediction and the label.

Recorded reliability

Observed accuracy versus the logged pre-review confidence, using only 280 revealed labels. Hidden labels are not used.

40–60% confidencen=10
Logged 55%Observed 60%
60–80% confidencen=30
Logged 68%Observed 53%
80–100% confidencen=240
Logged 98%Observed 96%

Recorded rolling metrics at this cycle: Brier 0.092 · ECE 0.033.

Matched evaluator-only windows

First 70 vs last 70 items, each scored against frozen simulated reference labels, evaluator-only; never learner feedback.

Accuracy 77% → 96% (rejecting everything would score 84% → 84%) · Brier 0.273 → 0.085 · ECE 0.101 → 0.034.

This permits equal-window comparison across modes; it was not learner-visible feedback.