Distance Matrix
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-07.)
Distance Matrix has 9 facts recorded in Dontopedia across 4 references, with 1 live disagreement.
Mostly:rdf:type(2), visualizes proximity(1), has beautiful structure(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (5)
Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.
rdf:typeRdf:type(2)
- D Matrix
ex:D-matrix - Variable D
ex:variable-D
discussesDiscusses(1)
- Chat Message 1
ex:chat-message-1
includesPanelIncludes Panel(1)
- All Three Codec Panels
ex:all-three-codec-panels
returnedByReturned by(1)
- Search Results
ex:search-results
Other facts (8)
The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.
| Predicate | Value | Ref |
|---|---|---|
| Rdf:type | Visualization Panel | [2] |
| Rdf:type | Search Result Array | [3] |
| Visualizes Proximity | Nearby Bytes | [1] |
| Has Beautiful Structure | Null | [1] |
| Shows Block Diagonal | Ascii Boundaries | [1] |
| Described As | Beautiful Structure | [2] |
| Contains | Distance Values | [3] |
| Is Output of | Search Operation | [4] |
Timeline
Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.
References (4)
ctx:discord/blah/watt-activation/part-420ctx:discord/blah/watt-activation/418- full textwatt-activation-418text/plain3 KB
doc:agent/watt-activation-418/4d0a6474-c481-4f12-889a-9e27f1035c4cShow excerpt
[2026-03-19 22:31] xenonfun: ⏺ All three codec panels rendering with real data: - Constellation Scatter: 256 bytes projected to 2D PCA. Clear structure already — lowercase (green) forms a distinct arc at the bottom, uppercase (blue) cl…
ctx:claims/beam/5b630b30-be7c-4e71-9257-76d31088943e- full textbeam-chunktext/plain1 KB
doc:beam/5b630b30-be7c-4e71-9257-76d31088943eShow excerpt
index = faiss.IndexIVFPQ(quantizer, 128, nlist, m, nbits) # Train the index index.train(vectors) # Add vectors to the index index.add(vectors) # Set the number of probes index.nprobe = nprobe # Search for the nearest neighbors D, I = in…
ctx:claims/beam/276709e4-43dc-4dfa-a983-c23bf40e789f- full textbeam-chunktext/plain1 KB
doc:beam/276709e4-43dc-4dfa-a983-c23bf40e789fShow excerpt
- Try different values for `nlist` and `nprobe` to find the optimal balance between speed and accuracy. - For example, you might try `nlist = 200` and `nprobe = 5` or `nprobe = 20`. 2. **Monitor Performance**: - Use `time` or `cPr…
See also
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