# Human Signals and False Positives

Use this guide when judging whether prose is genuinely owned, when comparing a revision to an author baseline, or when a pattern list is creating false confidence.

## Contents

- Provenance beats style
- Revision ownership
- Positive texture
- Ineffective indicators
- Multilingual and neurodivergent confounds
- Detector and judgment limits
- Moving-target problem
- Practical evidence ladder

## Provenance beats style

The strongest evidence about authorship comes from provenance:

- dated drafts and notes;
- source annotations;
- version history;
- tracked revisions;
- recorded interviews or observations;
- a known writing sample from the same author;
- the author’s ability to explain choices and correct errors;
- timestamps that predate the availability of the suspected tool.

Text written before public access to a model cannot have been produced by that model, even if it contains modern stereotypes. Historical writers used em dashes, tricolons, formal transitions, ornate vocabulary, and conclusion sections.

## Revision ownership

An author who owns a passage can usually answer questions such as:

- Why is this example here?
- Which source supports this clause?
- Why did you choose this level of certainty?
- What did the earlier draft say?
- Which part are you least sure about?
- Why does this paragraph precede the next one?
- Which sentence sounds most like you, and which does not?

The goal is not interrogation. These questions recover intention and often produce the best revision material.

**Case:** A URL looks fabricated. Ask how it was collected. If the author can locate the correct report, identify the typo, and point to the supporting passage, that is more informative than the visual shape of the URL.

## Positive texture

Human writing often contains a mix that optimization tends to smooth out:

- a precise, slightly odd detail;
- uneven emphasis based on what the author actually cares about;
- a plain repeated noun instead of forced synonyms;
- direct `is`, `are`, and `has` constructions;
- plain verbs such as `wrote`, `used`, `moved`, `tried`, and `died`;
- a real hedge such as `perhaps`, `tends to`, or `we do not know`;
- a strong claim the evidence earns;
- an isolated long or awkward phrase amid otherwise clear prose;
- a sentence fragment used for timing or voice;
- a local idiom, professional shorthand, or culturally specific reference;
- an honest admission of what the author could not verify;
- a concrete preference that another reasonable writer might not share.

Do not add fake messiness. Preserve real texture from the author’s drafts and supplied material.

## Ineffective indicators

These do not meaningfully establish authorship by themselves:

### Perfect grammar

Editors, translators, language professionals, careful students, and assistive tools can produce flawless grammar.

### Mixed casual and formal register

Code-switching, youth, playfulness, technical background, neurodivergence, collaborative documents, and multiple editors can all create register shifts.

### “Bland,” “robotic,” “fancy,” “academic,” or “formal” tone

These labels are impressions, not features. Name the actual issue: abstract nouns, unsupported claims, repeated syntax, missing actors, genre mismatch, or thin evidence.

### Transition words in isolation

`Additionally`, `Consequently`, and `Notably` can be overused, but transitions are ordinary tools. Look at density, placement, and whether the relationship is real.

### Unsourced content

Humans have written unsourced material for centuries. Modern models can also produce citations. Verify the claim and source instead of treating citation count as provenance.

### Correct or bizarre markup

Visual editors, extensions, importers, platform bugs, experienced users, and beginners all create distinctive syntax. Only specific internal artifacts strongly tie text to a tool.

### Curly quotes or em dashes

Professional typesetting, Word, macOS, iOS, house style, and personal taste account for both. Review fit and density, not authorship.

## Multilingual and neurodivergent confounds

Writers working in an additional language may:

- avoid repeating a noun because they were taught to vary vocabulary;
- mix national varieties of English;
- prefer formal transitions;
- use dictionary-selected synonyms;
- produce unusual article, preposition, or punctuation patterns;
- write more formally in public than in private messages.

Neurodivergent writers may use repeated structures, explicit transitions, unusual precision, intense formality, or mixed emotional and clinical registers. Do not punish these voices by “humanizing” them into a generic conversational norm.

Ask what the author wants to preserve. Edit for reader access and purpose, not conformity.

## Detector and judgment limits

Automated detectors can fail across unseen models, domains, sampling settings, paraphrases, and adversarial modifications. Human readers also make errors, and expertise is uneven. A detector score is not a writing objective.

For high-stakes work:

1. Check the applicable AI-use and disclosure policy.
2. Preserve draft history and source notes.
3. Verify claims and citations.
4. Compare with the author’s baseline.
5. Ask the author to explain material choices.
6. Report uncertainty rather than making a style-based accusation.

## Moving-target problem

Model vocabulary and formatting change after public criticism, product updates, system prompts, and user habits. Human language also absorbs model-associated phrases. Different models have distinguishable idiolects; there is no single permanent “AI voice.”

Therefore:

- date pattern claims;
- distinguish historical cues from current ones;
- keep platform-specific artifacts separate from general craft issues;
- prefer source fidelity and genre fit over stereotype matching;
- update scripts without pretending the new list is complete.

## Practical evidence ladder

From strongest to weakest for provenance questions:

1. Direct internal artifact or verifiable tool trace.
2. Draft history, metadata, source notes, or explicit disclosure.
3. Fabricated or mismatched citations combined with other evidence.
4. Sudden style change against a reliable author baseline.
5. A cluster of independently observed lexical, syntactic, structural, and formatting patterns.
6. One phrase, punctuation mark, transition, or subjective impression.

For ordinary editing, provenance may not matter. Fix the false claim, vague sentence, broken citation, bad flow, or mismatched tone because it harms the reader.
