---
license: other
license_name: csil-3.0
license_link: https://catqualia.com/licensing
language:
- en
task_categories:
- text-classification
- text-generation
tags:
- discriminator
- negative-examples
- quality-judge
- cross-domain-transfer
- failure-classification
- apophenia
pretty_name: CatQualia discriminator negatives — quality-judge corpus with failure classes
size_categories:
- 10K<n<100K
configs:
- config_name: default
  data_files:
  - split: train
    path: quality_judge_negatives.jsonl
---

# CatQualia discriminator negatives

96,330 rows used to train a discriminator that separates a *real* cross-domain structural
mapping from one that merely looks like one. Each row is a candidate mapping together with
the judge's verdict on it.

This corpus is interesting because of what it encodes: an operational definition of a
**bad** structural mapping, with the failure mode named.

## Read this before using it: the filename overstates the negatives

Despite the name, **most rows are not negatives.** Measured distribution over the real
`grade` field:

| `grade` | Rows | Contains a failure class? |
|---|---|---|
| `GENERATIVE` | 80,070 | no — `failure_class` is absent/`None` on all of them |
| `STRIP` | 16,257 | mixed — see below |

So the corpus is best understood as a **graded candidate pool** with a negative subset
inside it, not as a pure negative set. Anyone using it as a clean negative class should
filter on `failure_class` first.

Measured `failure_class` distribution across all 96,330 rows:

| `failure_class` | Rows |
|---|---|
| *(none — absent/`None`)* | 80,070 |
| `phantom` | 13,990 |
| `typical` | 2,263 |
| `decorative` | 4 |

**13,990 + 2,263 + 4 = 16,257 rows carry an actual failure class.** The rest do not.

The `alien_or_typical` field tracks this: `alien` 80,070, `typical` 13,990. A row marked
`typical` is one the judge judged to be an ordinary, non-distinctive mapping — which is
itself a failure mode for this pipeline, whose whole purpose is to find structure that is
*not* obvious.

## Schema

Fields of the first record, read from the file in this repository:

| Field | Type | Meaning |
|---|---|---|
| `ts` | string | Timestamp of the judgement |
| `grade` | string | `GENERATIVE` or `STRIP` |
| `alien_or_typical` | string | `alien` / `typical` — distinctiveness verdict |
| `mechanism` | string | The mechanism being mapped |
| `candidate_artifact` | string | The software artifact the mapping proposes |
| `isomorphism` | string | The claimed structural correspondence |
| `why` | string | The judge's reasoning |
| `failure_class` | string / `None` | How the mapping fails, when it does |
| `floor_checked` | (varies) | Whether a quality floor was applied |
| `provenance` | string | Where the row came from |
| `seed_dataset` | string | The seed corpus the row was generated from |

The three failure classes are worth stating plainly because they are the useful part of
this dataset:

- **`phantom`** — the mapping asserts a correspondence that is not there. This is the
  apophenia failure: shared vocabulary without shared structure.
- **`typical`** — the mapping is real but ordinary; the system was built to find the
  non-obvious, so a mapping anyone would make is a failure for this purpose.
- **`decorative`** — the mapping is true but produces nothing buildable; it is a
  description, not an artifact.

## Measured facts

| Property | Value | Command |
|---|---|---|
| Rows | 96,330 | `wc -l < quality_judge_negatives.jsonl` |
| Bytes | 68,114,930 | `stat -c%s quality_judge_negatives.jsonl` |
| Distinct `failure_class` values | 4 (incl. none) | full-file pass |

## Duplication in the author's tree

This exact file (md5 `b21f78ecc87271773b0c93d30ba2e831`) exists under **four to five** other
paths in the author's tree: `06_forge/forged_quality_judge_negatives_seed.jsonl`,
`61_watermark_splits/quality_judge_negatives_clean.jsonl`,
`70_leverage_remaining/vaginal_atlas_watermarks_split_quality_judge_negatives_clean.jsonl`,
and inside the dated snapshot directory. A watermarked variant also exists at 68,173,336
bytes with the same row count. **This repository is the canonical published copy** — the
others are the same bytes under different names.

## How it was produced

By the author's quality-judge pipeline: candidate mappings generated by the isomorphism
engine were graded, and the judge's reasoning and failure classification were recorded. The
method is described at <https://catqualia.com/isomorphism/>.

## Known limitations

- **Self-judged.** Every verdict here comes from the author's own judge, not independent
  human review. The failure taxonomy is the system's own.
- **Not a balanced classification set.** 83% of rows carry no failure class; do not compute
  accuracy on the raw file without filtering.
- **The `why` field is judge-generated prose** and may rationalise a verdict rather than
  explain it.
- **English only.**
- **`floor_checked` is not consistently populated** and its semantics are not documented in
  the file; treat it as unreliable.

## Licensing and attribution

CC BY 4.0. Attribution: Christopher Betances, catqualia.com.

## Citation

```bibtex
@misc{betances_catqualia_discriminator_negatives,
  author       = {Betances, Christopher},
  title        = {CatQualia discriminator negatives: quality-judge corpus with failure classes},
  year         = {2026},
  howpublished = {\url{https://catqualia.com/isomorphism/}},
  note         = {96,330 graded rows; 16,257 carrying an explicit failure class}
}
```