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deep focus

technique using a large depth of field
Intangible technique Q1182433
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deep focus

Summary

deep focus is a technique[1]. It draws 207 Wikipedia views per month (technique category, ranking #67 of 416).[2]

Key Facts

  • deep focus's instance of is recorded as technique[3].
  • deep focus's Freebase ID is recorded as /m/07f1cj[4].
  • deep focus's Microsoft Academic ID is recorded as 2775878524[5].

Why It Matters

deep focus draws 207 Wikipedia views per month (technique category, ranking #67 of 416).[2] It has Wikipedia articles in 8 language editions, a strong signal of global cultural recognition.[6] It is known by 7 alternative names across languages and contexts.[7]

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [3] ↑ . wikidata.org.
  2. [4] ↑ . Freebase Data Dumps. wikidata.org.
  3. [5] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

Aggregate / graph-position facts

  1. [2] ↑ . Wikimedia Foundation. dumps.wikimedia.org.
  2. [6] ↑ . Wikidata sitelinks. wikidata.org.
  3. [7] ↑ . Wikidata aliases. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). deep focus. Retrieved May 3, 2026, from https://4ort.xyz/entity/deep-focus
MLA “deep focus.” 4ort.xyz Knowledge Graph, 4ort.xyz, 3 May. 2026, https://4ort.xyz/entity/deep-focus.
BibTeX @misc{4ortxyz_deep-focus_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{deep focus}}, year = {2026}, url = {https://4ort.xyz/entity/deep-focus}, note = {Accessed: 2026-05-03}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): deep focus — https://4ort.xyz/entity/deep-focus (retrieved 2026-05-03)

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