Deep dive — chart 3

Chart 3 — lane rate per asset group, baseline vs recent

The chart with the sustainment + safety-of-flight bite. Where score-distribution shifts translate into actual asset routing. F3 red_ground_urgent rate collapsed 34% → 8%. Other asset groups stable. That is the exact SAFETY UNDER-flagging signature JAG + GAO look for.

Maintenance-lane rate per asset group, baseline vs recent

Maintenance-lane rate per asset group — baseline (left) vs recent (right). F3 red_ground_urgent rate collapsed while other groups stayed stable.

What you are looking at

Grouped bars per asset group (F1 / F2 / F3 / F4 / F5)
Three colors per group: Green Mission-Capable / Yellow Watch-Scheduled / Red Ground-Urgent
Left cluster: baseline (first 30 days) — the "normal" routing per group
Right cluster: recent (last 30 days) — the current routing per group

What the chart shows

F1, F2, F5 — lane rates unchanged between baseline and recent.
F4 — small directional drift (late-life airframe distributional stress) but well within tolerance.
F3 — red_ground_urgent rate collapses (34% baseline → 8% recent). Green_ready and yellow_watch rates absorb the shifted mass.
The differential exists only for F3. Other operational groups are unaffected.

26 percentage-point differential in red_ground_urgent routing. One asset group. Silently. Over 45+ days. In the WRONG direction — assets that should have been grounded were not. Over ~1,000+ F3 assessments in the drift window, roughly 270 assets that baseline expectations would have red-lane routed were silently down-scored to yellow-watch or green-ready.

Why aggregate metrics missed it

Because F3 is one asset group among five, the aggregate red-lane count barely moved: the F3 collapse rounded to noise across the whole fleet. That is why the fleet-readiness dashboard stayed green. Aggregate metrics are inherently blind to group-differential patterns, and group-differential patterns are inherently what disparate-impact + safety-of-flight-precursor analysis is built to surface.

The high-severity-event count that fired the determination

12 high-severity distributional-drift events across the 90-day window — F3 KL-divergence exceeded 1.0 on Days 44, 51, 58, 65, 72, 79, and 86, plus F4 divergence on Days 51, 58, 65, 79, and 86. Once event count exceeds 3 high-severity, the Snapshot lands on Category C by rule — no matter what any other metric shows.

See the A/B/C decision logic →

The exhibit-quality read

This chart is what a JAG accident-investigation-board or GAO auditor asks the program office for first when an AI-driven readiness call appears on the timeline of an incident. It is also what the program office's own Contracting Officer should have on file before either lands — because the same chart, in the program office's hand, tells a different story:

Same chart, program-office stance: "we identified this pattern through independent verification on Day X, initiated the following remediation on Day X+N, notified the Contracting Officer on Day X+M, and here is the timeline of that remediation." The chart becomes evidence of good-faith diligence, not evidence of missed monitoring.

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Same lane-shift chart for your program office's actual AI surface + full determination + 3 fix-first items.

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