Fission / Fusion
Split any source or entire data load into visible, editable evidence fragments. Select exactly what survives. Then recombine those fragments into a calculated result without losing their parent lineage.
Fission → Fusion → New datasets
Data becomes something new.
Combine compatible sources into weighted EFV profiles. Reveal disagreement, change over time, and which origins move the result.
Connecting to your private datasets…
What the data reveals
Waiting for a discovery snapshot…
Patterns retain their sources. Forward tests are judged only against later compatible observations. EFV describes structural indices.
How research attention improves
What agents need next
Checking evidence requirements…
Prioritized by believability weight and the evidence gap. New observations update these tasks. A cleared condition does not prove a claim.
Across data types
Give sources shared context
Record the same subject or event ID across sources, plus event or observation time with a time zone. For location-based matches, retain the place’s role, coordinates and precision. Similar names alone do not establish a match.
Review source context
Only fill the fields you want to correct. These private, owner-reported annotations affect fusion grouping. Original measurements and believability stay unchanged.
Context correction history
Undo restores the original source context. Superseded corrections stay in the audit trail. Changed source versions require a new review.
How these datasets are created
Sources are split into timestamped E/F/V observations. Fusion requires the same entity or exact location, time window, modality and measurement method. Without an entity or location, the row describes the workspace collection. Multi-modal observations can be linked by a shared entity and time; their measurements stay separate.
Believability increases contribution weight by up to 3× including the baseline. Duplicate lineage counts once; each origin's total weight is capped at its strongest input. Different origins are not proof of independent verification. Disagreement and source-removal sensitivity are displayed alongside each result.
These are calculated, private datasets. EFV and visual motion are structural indices, not physical Hz. Original measurements stay unchanged. Saving a row to NOUS keeps it labeled as derived. New source arrivals trigger a throttled rebuild; the bounded workspace source window is also checked once a minute while enabled.
Manual transformation workbench
OMNIA Flow · repeatable transformation
Load any data
1 · Source and partition rules
2 · Fusion recipe
Transformation Agent · create, modify, loop
Original source
Parsed fragments · click to include or exclude
Fusion output
Selected fragment editor
Lineage receipt
Claim IntelligenceTrace the statement. Inspect the sources. Follow the outcome.
See what connects.
One continuous path from a public statement to reusable knowledge.
Give your data a track record.
Track a claim to see real sources and outcomes connected here. No example findings are mixed into your data.
Owner-reviewed outcomes · Connections show recorded lineage, not causation. Motion is decorative; it does not represent measured EFVT or live transfers.