迈向所有现存爬行动物物种的数字化描述

Megataxa Pub Date : 2023-10-31 DOI:10.11646/megataxa.10.1.6
PETER UETZ, YAA ADARKWA DARKO, DUSTIN ZELIFF
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引用次数: 0

摘要

脊椎动物数据库在数字化物种描述方面进展缓慢。其中,爬行动物数据库(http://www.reptile-database.org)收集了约3000种蛇、约5000种蜥蜴、约150种乌龟和鳄鱼的约8000种描述。在这里,我们讨论这些数据如何有助于特征分析,物种鉴定,以及与其他数据源(如公民科学观察)的整合(这取决于正确的鉴定)。重要的是,这里描述的数据可以作为机器学习项目的训练数据,我们提供了使用ChatGPT进行物种比较的示例。虽然这些人工智能驱动的比较仍然是错误的,但我们预计在不久的将来会有实质性的改进。我们要求爬虫界帮助完成我们的物种描述公共收集,并建议其他物种数据库效仿并为其分类群提供类似的数据。
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Towards digital descriptions of all extant reptile species
Vertebrate databases have been slow to digitize species descriptions. One of them, the Reptile Database (http://www.reptile-database.org), has accumulated ~8,000 species descriptions for ~3,000 species of snakes, ~5,000 species of lizards, and ~150 species of turtles and crocodiles. Here we discuss how this data contributes to character analysis, species identification, but also to integration with other data sources such as citizen science observations (which depend on correct identifications). Importantly, the data described here may serve as training data for machine learning projects and we present examples of species comparisons using ChatGPT. While these AI-driven comparisons are still erroneous, we expect substantial improvements in the near future. We request the herpetological community to help complete our public collection of species descriptions and suggest that other species databases follow suit and provide similar data for their taxa.
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