Datasets:

NagaYu
/

dendro-lowbackground

---
license: cc0-1.0
task_categories:
- text-classification
- text-generation
language:
- en
size_categories:
- 1K<n<10K
tags:
- provenance
- low-background
- data-curation
- dataset-contamination
- dendro
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---
# Dendro low-background corpus

5034 arXiv records annotated with **archival evidence of when they existed**, produced by
[Dendro](https://github.com/NagaYu/dendro) v0.1.0.

2500 of them (49.7%) are **low-background**: an independent registration record
places them before 2021-01-01, i.e. before large-scale text generation. The name is from
metallurgy — low-background steel is steel smelted before the 1945 atmospheric tests: not
special steel, just ordinary steel that happens to predate the contamination, and valuable
because no amount of later care can reproduce it.

## Read this before you use it

- **This is not an AI-writing detector, and these columns must not be used as one.** They
  report *evidence that content existed before a date*. Nothing here supports a conclusion
  that a particular person did or did not write something.
- **Absence of evidence is not evidence.** Most text that has ever existed was never archived.
  `dendro_abstained` marks rows where the evidence is too thin to act on — those are
  *unknown*, not *generated*.
- **Every row is witnessed by arXiv and arXiv alone.** `dendro_operators` is 1 throughout, and
  `dendro_flags` contains `single_operator`. Compromising one organisation would be sufficient
  to move every date in this dataset. Dendro's whole argument is that confidence should come
  from *independent operators*; this corpus has one, and the column says so rather than
  hiding it.
- **The recent split is "human-attributed", not "verified human".** By 2025 an unknown share
  of abstracts have been through a model. There is no clean recent human corpus to be had —
  which is the argument for dating by archive rather than by inspection.
- **Selection is not neutral.** Archived text over-represents what crawlers reached: English,
  institutional, indexed, long-lived. A low-background subset concentrates every one of those
  biases.

## Columns

| column | meaning |
|---|---|
| `text` | title + abstract, as fingerprinted |
| `title`, `doi` | the record's own metadata |
| `url`, `arxiv_id`, `category`, `era` | identifiers and provenance of the record |
| `published` | arXiv v1 submission date — the witness |
| `dendro_not_after` | date the content is **proven to have existed by** |
| `dendro_not_after_year` | integer year, convenient for filtering |
| `dendro_human_origin_p` | calibrated probability — **not** a label |
| `dendro_ci_low` / `dendro_ci_high` | 90% credible interval, the honest width of the claim |
| `dendro_abstained` | true when the evidence is too thin to act on |
| `dendro_operators` | count of *independent* operators behind the bound |
| `dendro_evidence_logodds` | how hard the bound would be to forge |
| `dendro_flags` | detected inconsistencies |
| `dendro_explanation` | human-readable receipt naming the witness sources |
| `low_background` | proven pre-2021 existence **and** `dendro_ci_low` ≥ 0.8 |

### Why the threshold is 0.8 and not 0.95

Because that is what the evidence in *this* corpus can actually support, and moving the
threshold to flatter the number would be the whole problem with provenance tooling.

Every row here rests on **one operator**. Under Dendro's model a single arXiv registration
gives an evidence log-odds of ~6.5, which puts the *lower* end of the 90% credible interval at
about 0.85 no matter how trustworthy arXiv is — the interval is wide because corroboration is
absent, not because the record is doubtful. At `ci_low ≥ 0.90` this dataset would contain
**zero** low-background rows, which is a true statement about single-operator evidence and a
useless artefact.

So the flag is set where single-operator registration evidence genuinely reaches, and the
number that would tighten it is `dendro_operators` — not the threshold. A document witnessed
by arXiv *and* the Internet Archive *and* Common Crawl clears 0.95 comfortably; filter on
`dendro_ci_low` yourself if you want a different line.

There is deliberately **no** `is_synthetic` column and no boolean verdict. Code that wants a
filter must pick a threshold explicitly, and should prefer `dendro_ci_low` so the choice is
conservative.

## Three lines to use it

```python
from datasets import load_dataset
ds = load_dataset("NagaYu/dendro-lowbackground", split="train")
clean = ds.filter(lambda r: r["low_background"])          # 2500 rows
```

## Purity / retention trade-off

Selecting to bound the *expected* synthetic fraction (provably maximum-cardinality — see
`dendro.corpus_report.build_low_background_subset`):

| max expected synthetic | rows kept | retention |
|---|---|---|
| ≤ 1% | 0 | 0.0% |
| ≤ 2% | 0 | 0.0% |
| ≤ 5% | 0 | 0.0% |
| ≤ 10% | 0 | 0.0% |
| ≤ 20% | 2790 | 55.4% |

## Method, in one paragraph

Dendro asks independent archives — the Internet Archive, Common Crawl, arXiv, Crossref, public
posting archives — what they observed and when, groups witnesses by **operator** rather than by
count (twenty captures from one archive are one archive), and reports the earliest time whose
surviving evidence clears a failure-probability budget. It never reads the prose, which is why
its accuracy does not move when a new generator ships. Probabilities are produced by a mixture
that collapses to the base rate when evidence is absent, so "no evidence" cannot be reported as
"synthetic".

The calibrator is **left unfitted here on purpose**: a fitted map encodes the base rate of the
corpus it was fitted on, and baking that into a published artefact would make every row depend
on a split nobody downstream can inspect. These are the raw numbers.

## Provenance of the data itself

arXiv metadata, including abstracts, is offered under
[CC0 1.0](https://info.arxiv.org/help/api/tou.html) through the public API and OAI-PMH, which
is how it was harvested. Thank you to arXiv for use of its open access interoperability.

Generated 2026-08-10 by `scripts/publish_dataset.py` · Apache-2.0 code, CC0 data.

	---
	license: cc0-1.0
	task_categories:
	- text-classification
	- text-generation
	language:
	- en
	size_categories:
	- 1K<n<10K
	tags:
	- provenance
	- low-background
	- data-curation
	- dataset-contamination
	- dendro
	configs:
	- config_name: default
	data_files:
	- split: train
	path: data/train-*
	---

	# Dendro low-background corpus

	5034 arXiv records annotated with archival evidence of when they existed, produced by
	[Dendro](https://github.com/NagaYu/dendro) v0.1.0.

	2500 of them (49.7%) are low-background: an independent registration record
	places them before 2021-01-01, i.e. before large-scale text generation. The name is from
	metallurgy — low-background steel is steel smelted before the 1945 atmospheric tests: not
	special steel, just ordinary steel that happens to predate the contamination, and valuable
	because no amount of later care can reproduce it.

	## Read this before you use it

	- This is not an AI-writing detector, and these columns must not be used as one. They
	report evidence that content existed before a date. Nothing here supports a conclusion
	that a particular person did or did not write something.
	- Absence of evidence is not evidence. Most text that has ever existed was never archived.
	`dendro_abstained` marks rows where the evidence is too thin to act on — those are
	unknown, not generated.
	- Every row is witnessed by arXiv and arXiv alone. `dendro_operators` is 1 throughout, and
	`dendro_flags` contains `single_operator`. Compromising one organisation would be sufficient
	to move every date in this dataset. Dendro's whole argument is that confidence should come
	from independent operators; this corpus has one, and the column says so rather than
	hiding it.
	- The recent split is "human-attributed", not "verified human". By 2025 an unknown share
	of abstracts have been through a model. There is no clean recent human corpus to be had —
	which is the argument for dating by archive rather than by inspection.
	- Selection is not neutral. Archived text over-represents what crawlers reached: English,
	institutional, indexed, long-lived. A low-background subset concentrates every one of those
	biases.

	## Columns

	\| column \| meaning \|
	\|---\|---\|
	\| `text` \| title + abstract, as fingerprinted \|
	\| `title`, `doi` \| the record's own metadata \|
	\| `url`, `arxiv_id`, `category`, `era` \| identifiers and provenance of the record \|
	\| `published` \| arXiv v1 submission date — the witness \|
	\| `dendro_not_after` \| date the content is proven to have existed by \|
	\| `dendro_not_after_year` \| integer year, convenient for filtering \|
	\| `dendro_human_origin_p` \| calibrated probability — not a label \|
	\| `dendro_ci_low` / `dendro_ci_high` \| 90% credible interval, the honest width of the claim \|
	\| `dendro_abstained` \| true when the evidence is too thin to act on \|
	\| `dendro_operators` \| count of independent operators behind the bound \|
	\| `dendro_evidence_logodds` \| how hard the bound would be to forge \|
	\| `dendro_flags` \| detected inconsistencies \|
	\| `dendro_explanation` \| human-readable receipt naming the witness sources \|
	\| `low_background` \| proven pre-2021 existence and `dendro_ci_low` ≥ 0.8 \|

	### Why the threshold is 0.8 and not 0.95

	Because that is what the evidence in this corpus can actually support, and moving the
	threshold to flatter the number would be the whole problem with provenance tooling.

	Every row here rests on one operator. Under Dendro's model a single arXiv registration
	gives an evidence log-odds of ~6.5, which puts the lower end of the 90% credible interval at
	about 0.85 no matter how trustworthy arXiv is — the interval is wide because corroboration is
	absent, not because the record is doubtful. At `ci_low ≥ 0.90` this dataset would contain
	zero low-background rows, which is a true statement about single-operator evidence and a
	useless artefact.

	So the flag is set where single-operator registration evidence genuinely reaches, and the
	number that would tighten it is `dendro_operators` — not the threshold. A document witnessed
	by arXiv and the Internet Archive and Common Crawl clears 0.95 comfortably; filter on
	`dendro_ci_low` yourself if you want a different line.

	There is deliberately no `is_synthetic` column and no boolean verdict. Code that wants a
	filter must pick a threshold explicitly, and should prefer `dendro_ci_low` so the choice is
	conservative.

	## Three lines to use it

	```python
	from datasets import load_dataset
	ds = load_dataset("NagaYu/dendro-lowbackground", split="train")
	clean = ds.filter(lambda r: r["low_background"]) # 2500 rows
	```

	## Purity / retention trade-off

	Selecting to bound the expected synthetic fraction (provably maximum-cardinality — see
	`dendro.corpus_report.build_low_background_subset`):

	\| max expected synthetic \| rows kept \| retention \|
	\|---\|---\|---\|
	\| ≤ 1% \| 0 \| 0.0% \|
	\| ≤ 2% \| 0 \| 0.0% \|
	\| ≤ 5% \| 0 \| 0.0% \|
	\| ≤ 10% \| 0 \| 0.0% \|
	\| ≤ 20% \| 2790 \| 55.4% \|

	## Method, in one paragraph

	Dendro asks independent archives — the Internet Archive, Common Crawl, arXiv, Crossref, public
	posting archives — what they observed and when, groups witnesses by operator rather than by
	count (twenty captures from one archive are one archive), and reports the earliest time whose
	surviving evidence clears a failure-probability budget. It never reads the prose, which is why
	its accuracy does not move when a new generator ships. Probabilities are produced by a mixture
	that collapses to the base rate when evidence is absent, so "no evidence" cannot be reported as
	"synthetic".

	The calibrator is left unfitted here on purpose: a fitted map encodes the base rate of the
	corpus it was fitted on, and baking that into a published artefact would make every row depend
	on a split nobody downstream can inspect. These are the raw numbers.

	## Provenance of the data itself

	arXiv metadata, including abstracts, is offered under
	[CC0 1.0](https://info.arxiv.org/help/api/tou.html) through the public API and OAI-PMH, which
	is how it was harvested. Thank you to arXiv for use of its open access interoperability.

	Generated 2026-08-10 by `scripts/publish_dataset.py` · Apache-2.0 code, CC0 data.