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We study whether humans or machine learning (ML) classification models are better at classifying scientific research abstracts according to a fixed set of discipline groups. We recruit both undergraduate and postgraduate assistants for this task in separate stages, and compare their performance against the support vectors machine ML algorithm at classifying European Research Council Starting Grant project abstracts to their actual evaluation panels, which are organised by discipline groups. On average, ML is more accurate than human classifiers, across a variety of training and test datasets, and across evaluation panels. ML classifiers trained on different training sets are also more reliable than human classifiers, meaning that different ML classifiers are more consistent in assigning the same classifications to any given abstract, compared to different human classifiers. While the top five percentile of human classifiers can outperform ML in limited cases, selection and training of such classifiers is likely costly and difficult compared to training ML models. Our results suggest ML models are a cost effective and highly accurate method for addressing problems in comparative bibliometric analysis, such as harmonising the discipline classifications of research from different funding agencies or countries.

The Stewart platform is a typical parallel mechanism, used extensively in flight simulators with six degrees of freedom. It is rarely found in animals and has never been reported to regulate and control physiological activities. Now an equivalent Stewart platform structure is found in the honey bee (Hymenoptera: Apidae: Apis mellifera L.) abdomen to explain its three-dimensional movements. The stereoscope and scanning electron microscope are used to observe the internal structures of honeybees’ abdomens. Experimental observations show that the muscles and intersegmental membranes connect the terga with the sterna and guarantee the honey bee abdominal movements. From the perspective of mechanics, a Stewart platform is evolved from the lateral connection structure of the honey bee abdomen, and the intrasegmental muscles between the sternum and tergum function as actuators between planes of the Stewart platform. The extraordinary structure provides various advantages for a honey bee to complete a variety of physiological activities. This equivalent Stewart platform structure can also be used to illustrate the flexible abdominal movements of other insects with the segmental abdomen.

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