Study Selection Flow Reconciler

How to use Study Selection Flow Reconciler

A literature-review flow can look balanced while hiding missing reasons or decisions on duplicates. Audit the entered record lineage and stages before approving the count register.

1. Enter record IDs and explicit duplicate links.
2. Replay screening decisions and investigate missing reasons or impossible stages.
3. Adjudicate actual studies separately and compare counts with the source export; no scientific conclusion is generated.

Good to know

• Declarations are not scientific truth or review-standard compliance.
• Expert adjudication and full-text rights remain external.
• Independent local review of supplied records. No account/API access, AI, publication, outreach, source-truth verification, legal certification or income forecast.
• Each field is limited to 8,000 UTF-16 characters and each CSV to 100 data rows with the exact displayed header. Quoted commas/newlines and doubled quotes are accepted. Unsupported controls, unpaired surrogates, duplicate identities and invalid records are refused rather than silently removed. Ordinary decimal inputs have magnitude at most 999,999,999; the smallest supported nonzero magnitude is 0.000000001. Exponents are refused; whole counts use exact integer checks before numeric conversion. Results use exact rational arithmetic, with at most 18 decimal digits and an ellipsis when further fractional digits remain.
• Markdown and CSV are editable review exports. CSV retains unresolved records and apostrophe-prefixes spreadsheet-like formula text; review your real import settings. Tool outputs can contain your entered pseudonymous records, so inspect them before sharing.
• Independent deterministic ToolJovia workflow. Inputs stay in this browser. No vendor account, model call, upload, publication, outreach, payment, saved input or outside service is used. A local reconciliation does not validate source truth, customers, income or legal compliance.