肢体比例预测了灭绝的羊动物的水生习惯和软组织
Caleb M Gordon1, Lisa S Freisem2, Christopher T Griffin3
1Department of Earth and Planetary Sciences, Yale University, New Haven, CT, USA; Florida Museum of Natural History, University of Florida, Gainesville, FL, USA.
Current biology : CB
|November 21, 2025
概括
自然选择推动了哺乳动物和爬行动物的水生进化. 机器学习使用四肢测量准确地预测了灭绝的羊动物的水生习惯,揭示了进化模式.
科学领域:
- 进化生物学是进化的生物学.
- 古生物学的古生物学
- 机器学习 机器学习
背景情况:
- 哺乳动物和爬行动物显示出从陆地祖先的水生生活方式的反复演变.
- 过渡式化石通常具有模两可的特征,使水生习惯的确定变得复杂.
- 对于水生物种专业化的骨科相关性进行了辩论.
研究的目的:
- 开发和验证一种机器学习模型,用于预测已灭绝的羊动物的水生亲和关系.
- 测试数字间带,和水生习惯的骨质相关性.
- 为了澄清含糊不清的化石记录的化石物种的生态状态.
主要方法:
- 收集了11000多个子动物的肢体测量结果.
- 训练并测试了家族遗传物流回归模型,以预测水生动物的习惯.
- 使用接收器操作特征分析来选择最好的预测模型.
主要成果:
- 手的相对长度被证明是软组织和水生习惯的最准确预测指标 (准确率高于90%).
- 该模型成功地预测了许多化石物种的水生亲和关系.
- 鉴定了中 dinosaurs 和茎爬行动物的半陆地习惯, ichthyosauromorphs 的完全水生习惯,以及 sauropterygians, mosasaurs 和 theropods 的多种水生起源.
结论:
- 使用机器学习的四肢形态分析可以可靠地推断灭绝的羊水动物的水生习惯.
- 这项研究澄清了水生适应的进化历史,跨越了各种氨基酸血统.
- 揭示了水生与陆生羊动物的截然不同的四肢比例景观.
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