Enqueue a writer-pipeline job for an existing WriterSession. Returns immediately with a jobId; the orchestrator-worker claims it within ~5 seconds. Default section is step_7_5 — the auto-chain that replaces the three buttons in Step 7.5. Use get_writer_pipeline_status to poll until status is 'done', 'failed', or 'aborted'. Uses Science AI Journal credits.

Return the latest writer-pipeline job for a (sessionId, section). Use after start_writer_pipeline and poll every 5-10 seconds. Terminal statuses: 'done', 'failed', 'aborted'.

Pre-submission duplicate-publication and salami-slicing check. Cross-references the title + abstract against CrossRef, arXiv, medRxiv, bioRxiv, Unpaywall, and a 900k-paper institutional library in ~30 seconds. Returns a status (likely_published, uncertain, or not_found) with a confidence score and message. Free. Use before submission to catch accidental duplicates or to confirm a preprint hasn't been formally published yet.

Run one of the HAKEM specialist agents (methodology, language, figures, plagiarism, or literature) on a prepared agent prompt and return the structured editorial decision: score (1-10), verdict (Accept / Minor Revision / Major Revision / Reject), summary, strengths, concerns, detailed multi-section review, confidence band, and questions for the authors. Uses Science AI Journal credits. For the full 5-agent + synthesis flow, prefer the web UI at scienceaijournal.com/ai-review.

Recommend ranked target journals for a paper from a ~1,200-venue index. Each result includes a letter grade (A-F), a match percentage, tier (1-3), publisher, open-access status, 2-year mean citedness, predatory-journal flag, and 2-3 example similar papers that landed at that venue. Free — runs locally via FTS5 + topic-RAG, no LLM call. Use when the user asks 'where should I submit this paper' or wants to compare target venues before deciding.

Run a free, zero-LLM-cost pre-submission scoring of an academic paper. Returns predicted publication tier (Tier 1, 2, or 3 probability), the detected research field, and a confidence band. Backed by a local 33,000-paper library via FTS5 BM25. Use this when the user wants a fast sanity-check on whether a paper is ready to submit, or which tier of journal to target. Sub-second response. Free.

Surface research gaps + the most-cited and most-recent papers around a query. Returns cross-paper synthesis gaps first (LLM-derived, grounded in ≥ 2 papers), then catalogue-level single-paper gaps. Plus a field overview and ≤ 50 top-cited and ≤ 50 most-recent papers. Uses Science AI Journal credits; rate-limited to 10 requests/hour per IP. Use for early-stage research discovery, literature gap identification, and proposal scoping.