academic-pipeline

The Academic Pipeline is a specialized orchestrator designed for researchers, students, and academics who require a structured, human-in-the-loop workflow for paper production. Instead of attempting full automation, it coordinates a 10-stage process—including deep research, writing, two-stage peer review, and final integrity verification—to ensure scientific rigor. It bridges the gap between raw data and publication-ready manuscripts by enforcing quality gates at every transition. By integrating tools like deep-research and academic-paper-reviewer, it prevents common AI failure modes such as hallucinated citations, methodological fabrication, and logic gaps. The pipeline is ideal for researchers seeking to maintain high standards while accelerating their writing process through AI-assisted orchestration.

• Coordinates a 10-stage workflow: research, write, integrity check, review, revise, and final validation.

• Features mandatory user-confirmation checkpoints and reproducible quality gates for systematic consistency.

• Includes a 'Material Passport' system for session state tracking, context resets, and audit ledger generation.

• Generates a Paper Creation Process Record PDF to document human-AI collaboration history.

• Supports mid-entry, allowing users to start at specific stages like revision or citation checking.

• Enforces strict data-access levels and utilizes Semantic Scholar API for reference verification.

• Intended for researchers and academics; not a tool for automated content generation.

• Requires human oversight at each stage to review AI-generated materials and verify claim accuracy.

• Operates best when integrated with LaTeX or Word/Pandoc workflows for consistent formatting.

• Highly configurable via ARS_PASSPORT_RESET and other environment-level flags for advanced session management.

• Avoids AI-only shortcuts by requiring manual intervention for critical decision points and final approvals.