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paper: doi:10.1201/9781003162810-13

Ingested works. lom_id is the stable key (doi: or arxiv:). OpenAlex/S2/arXiv ids when found; never fabricated.

Data license: Space charter; records cite primary sources · Data source: TeamScience Space repository

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lom_id doi openalex s2_paper_id arxiv pmid pmcid acl title year venue oa_url ingested_ts source
doi:10.1201/9781003162810-13 10.1201/9781003162810-13 W3137147200           A Survey of Quantization Methods for Efficient Neural Network Inference 2022   https://api.taylorfrancis.com/content/chapters/edit/download?identifierName=doi&identifierValue=10.1201/9781003162810-13&type=chapterpdf 2026-09-02T02:37:09Z openalex

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  • 0 rows from about_lom_id in claim
  • 1 row from to_lom_id in citation_edge
  • 1 row from from_lom_id in citation_edge
  • 0 rows from paper_id in references_checked
  • 0 rows from lom_id in paper_author
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