Do experts make mistakes?: A comparison of human and machine identification of dinoflagellates
Do experts make mistakes?: A comparison of human and machine identification of dinoflagellates
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DOI：
10.3354/meps247017
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发表时间：
2003-01-01
影响因子：
2.5
通讯作者：
González-Gil, S
中科院分区：
文献类型：
--
作者：
Culverhouse, PF;Williams, R;González-Gil, S
作者提出了人类分类学家/生态学家在识别海洋甲藻时所面临的困难的证据。这对海洋水产养殖中有害藻华的工作尤其重要。它表明，这是很难为人们分类标本的物种具有显着的形态变异，也许与其他物种的形态重叠。在专家分类标签任务中，经过培训的人员可以达到67%至83%的自我一致性和43%的人与人之间的共识。经常从事特定辨别的专家可以返回84%至95%的准确度。一般来说，无论是人还是机器都不能期望对样本进行高度准确或可重复的标记。它还表明，自动化方法可以执行以及人类对这些复杂的分类。
The authors present evidence of the difficulties facing human taxonomists/ecologists in identifying marine dinoflagellates. This is especially important for work on harmful algal blooms in marine aquaculture. It is shown that it is difficult for people to categorise specimens from species with significant morphological variation, perhaps with morphologies overlapping with those of other species. Trained personnel can be expected to achieve 67 to 83% self-consistency and 43% consensus between people in an expert taxonomic labelling task. Experts who are routinely engaged in particular discriminations can return accuracies in the range of 84 to 95%. In general, neither human nor machine can be expected to give highly accurate or repeatable labelling of specimens. It is also shown that automation methods can perform as well as humans on these complex categorisations.