Fresh for Which Claim? Separating evidence age, source lineage and decision scope in supplier research

This working paper investigates how supplier research can distinguish evidence age, source lineage and decision scope. It combines a purposive literature and standards synthesis with three separate Python demonstrations using constructed fixtures. A scope regression shows that selecting the latest assertion by field and source alone can discard a different supplier or service; partitioning by entity and scope before historical selection prevents that specific loss. The modules passed 14, 13 and 10 separate assertions, not an integrated accuracy evaluation. Scope identifiers and lineage are manually supplied. No production qualification, customer outcome or empirical supplier accuracy is established. Mohammad Maani established the research direction, supervised the work, supplied methodological decisions and an explicitly author-reported shipping illustration, reviewed and accepted the scope-isolation interpretation and figure, and authorized publication. Independent human code replication or source-by-source verification is not asserted. OpenAI ChatGPT/Codex assisted research, synthesis, drafting, code and synthetic-test design and execution; OpenAI image generation produced the conceptual artwork. AI is not an author. This deposit is not peer reviewed. The author is Founder of QuickAIBuy and has a commercial interest in its development. Project: https://www.quickaibuy.com . Version 1.0 includes the manuscript and reproducibility materials. CC BY 4.0 applies to the manuscript, original diagram and synthetic materials; trademark and font-license exceptions are documented.