Nottingham Workflow Custom Process Templates
Evidence-first research writing

Research Paper Creator

The Research Paper Creator is an evidence-first writing workflow. Instead of generating a paper from a prompt in one step, ZeroThink builds a source ledger, maps claims to evidence, exposes gaps, runs critique passes, and lets the researcher approve each stage before synthesis.

The aim is to support serious research drafting where provenance, structure, and human judgement matter.

Create A Research Paper

Use this as the active writing surface. It can build an evidence plan first, then a structured draft, reviewer critique, or source ledger. It can use Groq, NVIDIA, OpenAI, Gemini, xAI, and Quantum lanes when the matching keys are saved in Studio -> Neural Vault.

Research rule: the creator should never invent citations. Unknown papers, missing DOIs, or unverified URLs must be marked as placeholders or source tasks.

For OpenAI, Gemini, xAI, and Quantum lanes, the account must be Pro or the API will fall back according to the ZeroThink server rules.

Output

Ready. Start with an evidence plan, inspect the source ledger, then draft after checking the claims.

Core Workflow

Why This Is Research-Facing

Deeper Provenance

Every source, claim, and synthesis step is tied back to a ledger where possible.

Researcher-in-the-loop Control

The researcher can steer, correct, validate, and approve before final synthesis.

Evidence-first Drafting

The workflow starts with literature and claims, not one-shot generation.

Multi-model Lanes

OpenAI, Gemini, xAI, Groq, NVIDIA, and QuantumZero can be selected for different research passes.

Structured Critique

Arguments, counterarguments, gaps, and reviewer-style critique happen before the final draft.

Nottingham Fit

This workflow supports the Nottingham research collaboration direction by connecting survey extension, topic-expert identification, generative UI, provenance tracking, and human validation into a single staged process. It is built for research teams, not just one-shot generation.

AI co-scientist workflows remain a long-term goal that becomes more credible after search, retrieval, full-text processing, evidence mapping, and provenance are stronger.