Claude Opus 4.1 vs GPT 5.4
tree_0011 · Welcome
Timeline
Arrow keys or j/k move between rounds.
Round Context
Welcome
Evaluation and correction of fertility data
Within the single-volume international project developed by the International Union for the Scientific Study of Population (IUSSP) in collaboration with UNFPA—created as a successor to earlier United Nations manuals on indirect demographic techniques—identify the chapter that specifically addresses the assessment and adjustment of fertility data derived from limited, deficient, or defective sources. Provide the chapter’s author, year of publication, full suggested citation (including all listed editors, publisher, and place of publication), and the direct URL where the chapter can be accessed.
Answer length: 200-300 words.
Show hidden checklists
- Identification of the specific chapter: 'Evaluation and correction of fertility data' + matches the fertility-focused methodological component of the IUSSP/UNFPA demographic estimation volume
- Correct attribution to Moultrie TA (2011) + confirmed as a chapter within the successor project to UN Manual X on indirect demographic estimation
- Correct chapter title related to evaluation and correction of fertility data
- Author: Moultrie TA
- Year of publication: 2011
- Full list of editors: Moultrie TA, Dorrington RE, Hill AG, Hill K, Timæus IM, and Zaba B
- Publisher: International Union for the Scientific Study of Population
- Place of publication: Paris
- Direct URL to the chapter
- Indication that it is part of the demographic estimation tools volume
The question uses deep logic by referencing the institutional collaboration (IUSSP and UNFPA) and its historical lineage from UN Manual X, without naming the specific website or page. This forces the agent to reason about the correct volume and thematic context. It then requires wide aggregation by demanding multiple scattered bibliographic details—author, year, editors, publisher, location, and URL—ensuring comprehensive retrieval rather than a single fact lookup.
Judgment
First, Deep Logic: Agent A correctly identifies the relevant chapter within *Tools for Demographic Estimation* and attributes it to Tom A. Moultrie, matching the fertility data evaluation focus of the IUSSP/UNFPA successor volume. Agent B identifies an entirely different chapter, wrong author (Sathar), wrong year (1984), wrong editors, wrong place of publication, and a different historical context—failing the core entity requirement. Second, Width/Completeness: Agent A provides the correct volume, editors, publisher (IUSSP), place (Paris), and URL, though it gives the wrong publication year (2013 instead of 2011) and a slightly altered chapter title. Agent B’s bibliographic details are largely incorrect and do not match the required checklist. Finally, User Experience: Agent A is well structured, clearly formatted, and provides a direct URL and contextual explanation. Agent B is also clearly written but grounded in the wrong work entirely. Because Agent A has a factual error (year), it cannot receive MUCH_BETTER, but it decisively outperforms Agent B, which fails Deep Logic. Therefore: A_BETTER.
Claude Opus 4.1
Anthropic
GPT 5.4
OpenAI