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Using machine learning to model nontraditional spatial dependence in occupancy data

Research article (Ecology, 2021) · cited 11× · AI/ML
academia openalex:W3210018437
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Using machine learning to model nontraditional spatial dependence in occupancy data

Summary

Using machine learning to model nontraditional spatial dependence in occupancy data is a scholarly article[1].

Key Facts

  • Using machine learning to model nontraditional spatial dependence in occupancy data's instance of is recorded as scholarly article[2].

References

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

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Using machine learning to model nontraditional spatial dependence in occupancy data. Retrieved May 24, 2026, from https://4ort.xyz/entity/using-machine-learning-to-model-nontraditional-spatial-dependence-in-occupancy-data
MLA “Using machine learning to model nontraditional spatial dependence in occupancy data.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/using-machine-learning-to-model-nontraditional-spatial-dependence-in-occupancy-data.
BibTeX @misc{4ortxyz_using-machine-learning-to-model-nontraditional-spatial-dependence-in-occupancy-data_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Using machine learning to model nontraditional spatial dependence in occupancy data}}, year = {2026}, url = {https://4ort.xyz/entity/using-machine-learning-to-model-nontraditional-spatial-dependence-in-occupancy-data}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Using machine learning to model nontraditional spatial dependence in occupancy data — https://4ort.xyz/entity/using-machine-learning-to-model-nontraditional-spatial-dependence-in-occupancy-data (retrieved 2026-05-24)

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