--- title: "Checking a Model's Claim Against a Source" description: "The cost of a wrong answer falls on whoever passes it on. Picking the claims that carry weight, finding them in a source that is not the model, and dropping what cannot be found is the whole of the ch" canonical: https://lightmysky.com/learn/computing/checking-a-models-claim-against-a-source-mt_Qh4Pnnfqv2 source: https://lightmysky.com/learn/computing/checking-a-models-claim-against-a-source-mt_Qh4Pnnfqv2.md retrieved: 2026-09-12 --- > **Agent view.** This is the Markdown twin of the page, for tools and assistants. > When to use this site, and the call that answers each job: https://lightmysky.com/agent-instructions.md > API description (OpenAPI 3.1): https://lightmysky.com/openapi.json · Authentication: https://lightmysky.com/auth.md > Pricing: https://lightmysky.com/pricing.md · Catalog: https://lightmysky.com/llms.txt · Full catalog: https://lightmysky.com/llms-full.txt > Every machine-readable file on this domain: https://lightmysky.com/.well-known/ai-catalog.json > Ask for Markdown with `Accept: text/markdown`, a `.md` address, or `?mode=agent`. # Checking a Model's Claim Against a Source The cost of a wrong answer falls on whoever passes it on. Picking the claims that carry weight, finding them in a source that is not the model, and dropping what cannot be found is the whole of the check. Subject: Computing · Area: Artificial Intelligence · Ages 15 to 16 Page: https://lightmysky.com/learn/computing/checking-a-models-claim-against-a-source-mt_Qh4Pnnfqv2 ## Ready when they can - Pick out which claims in an answer carry the weight, instead of checking every sentence - Find a named claim in an independent source, or record that it could not be found - Say why a reference the model produced is not evidence that the reference exists ## Lesson: Checking what a model tells you A wrong answer costs whoever passes it on: you. So check the claim, not the confidence. An answer can sound smooth and sure yet still be wrong. Pick out the statements that carry weight: names, dates, numbers, quotes, and the sources the answer points to. Small greetings and jokes can wait. The weight-carrying claims are the ones worth your checking time. Next, leave the original source. Open a fresh search and look for the same claim somewhere that did not produce it. If a model says a study exists, finding that study yourself is the check. Rereading the model's own sentence about it proves nothing. An independent source, or a clear note that none turned up, is the result you want. **Example.** Watch references most closely. A model can invent titles, authors, and links that look perfectly real. A reference the model produced is not evidence that the reference exists. Until you find the source with your own search, treat it as missing. The habit is simple: the model points, and you confirm elsewhere before you trust or repeat. **Tip.** End with a firm rule. If a claim shows up nowhere outside the model's answer, do not pass it on. Either say it could not be confirmed or leave it out. Dropping one shaky line beats spreading a confident error that lands on you. **Recap.** Weigh the claims, check them outside the model, and drop what you cannot find. ## Practice 8 questions on this page, each with its working shown. ## Needs first - [Writing a Prompt That Says What You Actually Want](https://lightmysky.com/learn/computing/writing-a-prompt-that-says-what-you-actually-want-mt_dJ5-SDX3Ck) - [Research & Source Evaluation](https://lightmysky.com/learn/english/research-and-source-evaluation-mt_Qcsl1Z1x0l) ## Opens up - [What You Owe a Reader When a Model Helped](https://lightmysky.com/learn/computing/what-you-owe-a-reader-when-a-model-helped-mt_VsUSovHzfI)