Volkmann Nina, Schmarje Lars, Koch Reinhard, Kemper Nicole
Institute for Animal Hygiene, Animal Welfare and Farm Animal Behavior (ITTN), University of Veterinary Medicine Hannover, Foundation, Hannover, Germany.
Department of Computer Science, Faculty of Engineering, Christian-Albrechts-University Kiel, Kiel, Germany.
Vet Res Commun. 2025 Aug 8;49(5):278. doi: 10.1007/s11259-025-10833-6.
This study investigated variations in assessing potential pecking injuries in turkey hens when annotating image excerpts. Three observers (OBS1, OBS2, OBS3) with different levels of previous knowledge - one with experience in pecking injuries in turkeys and two computer science students - rated a total of 24,912 image excerpts. The image excerpts were evaluated in work packages (2,076 images each) and were classified by the observers as either head injury (HI), skin injury in the feathered area of the body (SI), or no injury (NI). Two observers evaluated three packages (OBS1, OBS2: 6,228 image excerpts each) and OBS3 annnotated six work packages (12,456 excerpts). The percentage of the classifications in the chronological sequence of the observations was analyzed. Inexperienced observers (OBS2 and OBS3) both classified an average of 13% of the shown images as HI, 70% as SI, and 17% as NI. On average, OBS1 classified 12% of the images as HI, 60% as SI, and 28% as NI. Throughout the study, all observers classified more recordings into the NI class. Particularly, OBS1 with the most experience in evaluating pecking injuries showed a different assessment by rating more images (plus 5%) as showing NI over time (OBS2: plus 0.7%; OBS3: plus 2.2%). This result raises questions about whether divergent assessments always occur in repeated judgments and how this effect can be avoided.
本研究调查了在注释图像片段时评估火鸡母鸡潜在啄伤的差异。三名具有不同知识水平的观察者（OBS1、OBS2、OBS3）——一名有火鸡啄伤评估经验，两名是计算机科学专业学生——对总共24912个图像片段进行了评级。图像片段按工作包进行评估（每个工作包2076张图像），观察者将其分类为头部受伤（HI）、身体有羽毛区域的皮肤损伤（SI）或无损伤（NI）。两名观察者评估了三个工作包（OBS1、OBS2各评估6228个图像片段），OBS3注释了六个工作包（12456个片段）。分析了观察时间顺序中分类的百分比。经验不足的观察者（OBS2和OBS3）平均将所展示图像的13%分类为HI，70%分类为SI，17%分类为NI。平均而言，OBS1将12%的图像分类为HI，60%分类为SI，28%分类为NI。在整个研究过程中，所有观察者将更多的记录分类为NI类别。特别是，在评估啄伤方面经验最丰富的OBS1随着时间的推移对更多图像（增加5%）的评估显示为NI，呈现出不同的评估结果（OBS2：增加0.7%；OBS3：增加2.2%）。这一结果引发了关于在重复判断中是否总是会出现不同评估以及如何避免这种影响的问题。
