What is he best known for?
The fields of study he is best known for:
- Ecology
- Cognition
- Linguistics
His primary areas of study are Ecology, Mate choice, Zebra finch, Developmental psychology and Imprinting.
His work on Animal communication as part of his general Ecology study is frequently connected to Noise pollution, thereby bridging the divide between different branches of science.
His biological study spans a wide range of topics, including Sexual selection, Cognitive psychology and Reproductive isolation.
His Zebra finch study incorporates themes from Discrimination learning and Syntax.
Carel ten Cate has researched Developmental psychology in several fields, including Social relation, Demography and Preference.
His Context study deals with Communication intersecting with Streptopelia.
His most cited work include:
- A noisy spring: the impact of globally rising underwater sound levels on fish (529 citations)
- The impact of learning on sexual selection and speciation. (246 citations)
- Low-frequency songs lose their potency in noisy urban conditions (180 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Zebra finch, Communication, Zoology, Streptopelia and Ecology.
His research in Zebra finch intersects with topics in Developmental psychology, Finch, Singing and Songbird.
Carel ten Cate has included themes like Variation, Perception, Genus Streptopelia and Zebra in his Communication study.
His Zoology research integrates issues from Ethology, Competition and Interspecific competition.
His work deals with themes such as Context, Syrinx and Animal communication, which intersect with Streptopelia.
His Ecology study combines topics from a wide range of disciplines, such as Evolutionary biology, Allopatric speciation and Vinaceous dove.
He most often published in these fields:
- Zebra finch (24.17%)
- Communication (20.83%)
- Zoology (20.00%)
What were the highlights of his more recent work (between 2010-2020)?
- Perception (17.50%)
- Cognition (9.17%)
- Speech recognition (6.67%)
In recent papers he was focusing on the following fields of study:
Perception, Cognition, Speech recognition, Artificial grammar learning and Cognitive science are his primary areas of study.
His Perception study integrates concerns from other disciplines, such as Communication, Zebra finch and Comparative cognition.
His Zebra finch research is multidisciplinary, incorporating elements of Variation and Duration.
His work is dedicated to discovering how Cognition, Cognitive psychology are connected with Mate choice, Sexual selection, Preference, Cognitive skill and Argument and other disciplines.
In his research on the topic of Mate choice, Ecology is strongly related with Empirical evidence.
His Speech recognition research incorporates themes from Absolute pitch and Fundamental frequency.
Between 2010 and 2020, his most popular works were:
- The impact of learning on sexual selection and speciation. (246 citations)
- Low-frequency songs lose their potency in noisy urban conditions (180 citations)
- Revisiting the syntactic abilities of non-human animals: natural vocalizations and artificial grammar learning (105 citations)
In his most recent research, the most cited papers focused on:
- Ecology
- Cognition
- Linguistics
His primary areas of study are Ecology, Cognitive psychology, Cognition, Perception and Artificial grammar learning.
Carel ten Cate has researched Ecology in several fields, including Cultural transmission in animals and Phenomenon.
His study in Cognitive psychology is interdisciplinary in nature, drawing from both Context, Empirical evidence, Sexual selection, Mate choice and Reproductive isolation.
The Perception study combines topics in areas such as Probabilistic logic and Grammar.
His research investigates the connection between Syntax and topics such as Biolinguistics that intersect with issues in Communication and Speech recognition.
His work carried out in the field of Communication brings together such families of science as Discrimination learning and Duplex perception.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
