I Made AI Look at Traces. For Science
← All postsSeptember 27, 2026Benchmarks3 min readI Made AI Look at Poop. For Science.By Dawid KiełbasaIn this article +What I gave themLet's look at a few cluesOkay, who figured it out?Footprints were the hardestSo, is 37% any good? When I'm out picking mushrooms, I sometimes come across footprints, feathers, or a pile of poop and have no idea what animal left them.
- ▪← All postsSeptember 27, 2026Benchmarks3 min readI Made AI Look at Poop.
- ▪For Science.By Dawid KiełbasaIn this article +What I gave themLet's look at a few cluesOkay, who figured it out?Footprints were the hardestSo, is 37% any good?
- ▪When I'm out picking mushrooms, I sometimes come across footprints, feathers, or a pile of poop and have no idea what animal left them.
Hacker News (AI / LLM) files mainly under ai. We currently carry 6,854 of its stories.
Story provenance
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Labqoat |
| Canonical URL | https://labqoat.com/blog/what-animal-left-this |
| Publication time | Tue, 29 Sep 2026 14:41:47 +0000 |
| Retrieval time | 2026-09-29T14:46:39.149Z |
| Last seen | 2026-09-29T14:46:39.149Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | None |
| Cluster logic | Not yet clustered, or no peer story found in the clustering window. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
← All postsSeptember 27, 2026Benchmarks3 min readI Made AI Look at Poop. For Science.By Dawid KiełbasaIn this article +What I gave themLet's look at a few cluesOkay, who figured it out?Footprints were the hardestSo, is 37% any good? When I'm out picking mushrooms, I sometimes come across footprints, feathers, or a pile of poop and have no idea what animal left them. I've tried asking AI about these finds, but I was never sure how often it was actually right. It would give me an animal name, but I didn't know enough to check the answer myself. After testing AI on spider photos, I decided to test this too. I put together 400 photos of animal droppings and 1,600 photos of footprints, feathers, eggs, and bones. Deer droppings in Canada. One of the photos in the benchmark. Cropped.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Labqoat.
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