Editing Research/Fiction Writing/AI Prose Strengthen (section)

== Executive summary ==

# '''AI detectors are imperfect evidence, not proof.''' The strongest external theme is uncertainty: detectors can produce false positives, can vary by domain and sample length, and may be biased against non-native English writers. Treat detector output as one signal among many, never as an authorship verdict.
# '''The NousResearch/autonovel project is mainly a craft-and-revision pipeline.''' Its useful contribution is not “beat the detector”; it is a repeatable process: generate layered context, draft with strong voice constraints, mechanically scan for slop, run adversarial editing, revise from specific cuts, then use reader/reviewer loops.
# '''Low-quality AI prose has recurring signals.''' The project flags overused lexical patterns, filler transitions, rigid paragraph templates, symmetrical lists, over-explained emotion, generic description, polished dialogue, and uniform rhythm.
# '''Good prose is specific and accountable.''' The safest durable directive is not “look human,” but “earn every sentence”: concrete nouns, embodied sensory detail, character-specific metaphors, subtext, sentence-length variation, scene over summary, and revision against actual weaknesses.
# '''Transparency matters.''' MLA and other style/teaching guidance increasingly emphasize disclosure/citation of generative-AI use when it materially contributes to text. Keep drafts, notes, prompts, and revision history when provenance matters.