Core concepts

Four ideas explain almost everything about how Kapnetix Post behaves. Read these once and the rest of the product follows.

Confidence is fixability

A confidence score predicts how cleanly Kapnetix can fix a take or a region — not merely that something is wrong. This is the single most important thing to internalise: confidence is never an error meter.

You see the same confidence map at two moments, and they are deliberately symmetric:

• Before (predicted). On the Triage screen, confidence forecasts how much review effort to expect, so you can plan the work before spending a token.
• After (measured). On the Review screen, confidence grades the result Kapnetix actually produced, so you can verify it.

If a result can't be measured honestly, it's shown as unverified rather than given a fabricated score.

Raw is immutable · Clean vN is non-destructive

Your raw capture is never modified. Every cleanup run stacks as a new named version — Clean v1, Clean v2, and so on — and the version history is never collapsed. You can always compare a clean version against the raw, or against an earlier clean, and you can revert individual regions.

A run is a versioned batch of takes cleaned together; a single take's history shows the run versions that produced it.

The four-state taxonomy

Every take and every region carries exactly one of four states. Before categorises the raw capture and signals the review effort to expect; After grades the result with the same colour and rank.

State	Before label	Anticipated action	After label	Colour
Clean	Clean	No review needed	Cleaned ✦✦✦	● green
High confidence	High confidence	Minimal review	Cleaned ✦✦	● cyan
Low confidence	Low confidence	Review recommended	Cleaned ✦	● amber
Manual cleanup	Recommended manual cleanup	AI assists · you finish	Cleaned · finish manually	● red

What the states mean:

• Clean (green) — arrived clean, nothing to fix, kept as raw.
• High confidence (cyan) — auto-cleaned, high confidence in the result.
• Low confidence (amber) — cleaned, but with borderline regions worth a glance.
• Manual cleanup (red) — couldn't be auto-cleaned; the AI assists and you finish the pass.

Only Clean takes stay raw; everything else is scheduled for cleanup.

Confidence heat vs. status chips

The status chips above are categorical — one of four states. Separately, the brand pink → cyan gradient is the continuous per-frame confidence scale on the timeline and 3D viewer: cyan = high confidence (clean), pink = low (needs eyes), on a 0–100 scale where 0 means needs eyes and 100 means clean. Chips stay categorical; heat stays continuous.

Errors and the model that fixes each

Kapnetix diagnoses three error types, each repaired by a specific Track M model:

Error	What it is	Model
Gap	Missing markers / occlusion	Solve · Gapfill
Swap	Marker labels swapped	Solve · Relabel
Jitter	High-frequency noise	Solve · Denoise

The fix order is fixed

Repairs run in a fixed order, and it doesn't reorder:

1. Gaps first — complete the skeleton.
2. Swaps next — relabel on now-continuous trajectories.
3. Jitter last — smooth once positions are correct.

In Auto mode Kapnetix picks the model per issue and applies this order for you. In Assisted mode you scope the work — frame range, error types, markers, and solve constraints (bone-length lock, foot-plant lock, preserve finger contacts) — and the same order still holds. The governing rule throughout is the AI only touches what you scope.