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Enregistrement W4322616724 · doi:10.1242/jeb.245626

Welcome Matt and farewell Ken

2023· article· en· W4322616724 sur OpenAlexaffabout
Kathryn Knight

Notice bibliographique

RevueJournal of Experimental Biology · 2023
Typearticle
Langueen
DomainePhysics and Astronomy
ThématiqueSpace Science and Extraterrestrial Life
Établissements canadiensUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésPassionPsychologyHumanitiesArt

Résumé

récupéré en direct d'OpenAlex

As milestone years go, 2023 is a big one for Journal of Experimental Biology. Celebrating its 100th anniversary, the journal is looking forward to the future, and the arrival of Matthew McHenry as a new Monitoring Editor is a fabulous way to begin the year's events. ‘JEB is likely the first scientific journal that I read’, says McHenry, adding that he was thrilled and honoured when JEB Editor-in-Chief Craig Franklin invited him to join the team of Editors.Growing up in Pennsylvania, USA, McHenry remembers that his parents emphasised the importance of education and a series of inspiring biology teachers set him on course to study Biology at Vassar College, USA. There, he was introduced to the field of biomechanics by John Long, Jr. ‘John had such a profound influence on me over those 4 years’, says McHenry, crediting him with kindling the passion for biomechanics that still inspires him 30 years on. ‘I entered college not even being aware that professors conducted research and left with a desire to become an academic scientist. I was swept up in the excitement of collaborative research well before I was formulating novel questions of my own’, he says.After graduating from Vassar, McHenry joined Mimi Koehl at University of California, Berkeley, USA, where he investigated swimming in ascidian larvae. ‘I was exposed to Mimi's remarkable ability to weave approaches from engineering to address questions of broad biological significance’, McHenry says. During his time there, McHenry also collaborated with JEB Deputy Editor-in-Chief Sheila Patek on the evolution of swimming in ascidians. Periods of postdoctoral research followed with George Lauder (Harvard University, USA) and Sietse van Netten (University of Groningen, The Netherlands) before McHenry joined the Department of Ecology & Evolutionary Biology at University of California, Irvine, USA – where he remains today – in 2005. ‘I have worked with some fantastic scientists and wonderful people’, he says.Currently advising a team of one postdoctoral researcher, one graduate student and several undergraduates, McHenry works on sensing, control and biomechanics of aquatic animals. ‘[Our] lines of investigation are concerned with strategy in predator–prey interactions, the neuromechanics of crawling in sea stars and the sensory basis of fish schooling’, he says. And McHenry is enthusiastic about the opportunity that joining the JEB Editorial Team offers. ‘The first four of the five papers from my work in college were published in JEB, so it was the most important journal to me from the beginning’, he says, adding that he is also looking forward to working with the journal team, which includes old friends.It is also time to say farewell to a longstanding Monitoring Editor, Ken Lukowiak from the University of Calgary, Canada, who will be leaving the team in March 2023 after 19 years. ‘It's sad, but I also believe that it's time to move on and bring in new diverse people’, says Lukowiak. As a Professor at the University of Calgary, Lukowiak has had a longstanding interest in learning and memory, forged during his PhD with Jon Jacklet at State University of New York, Albany, USA, looking at the role of memory in the gill withdrawal reflex of the California sea hare, Aplysia californica. After 2 years of postdoctoral research at the University of Kentucky, Lukowiak initially joined McGill University, Canada, as an Assistant Professor. But he admits that in 1978 he was seduced by the mountains. ‘I went to a meeting in Calgary and visited the Rockies. I decided then that although I loved Montreal, I loved the mountains more, so I asked for a job. Calgary was just starting a new medical school and they needed people, so they said, “Sure, come on out”’, Lukowiak chuckles.Around that time, he also switched from working on Aplysia to pond snails. ‘Working with pond snails was much less expensive. We were moving into doing a lot of tissue culture work, growing cells to look at how connections are formed, and it turned out that freshwater snails were better than Aplysia for doing that’, he recalls. Since then, Lukowiak has focused on how memory is formed and enhanced and how animals learn innately. ‘My lab snails respond innately to a crayfish predator, even though they haven't seen a crayfish predator for 250 generations. But my [wild] pond snails in Alberta don't respond to crayfish because we didn't have crayfish here until very recently, so how do we get that [memory] in?’, says Lukowiak, who thinks that he is getting close to understanding the epigenetics behind memory formation.Reflecting on his time with the journal, Lukowiak says that the annual journal symposium, and getting to know the other Editors, was always a highlight. He will also miss looking at the papers that came across his desk, learning about subjects that he may not have encountered otherwise. And if he had one piece of advice to pass on to a new Editor? ‘Be open to new ideas’, Lukowiak says, mentioning a recent publication in Nature. ‘It said that we're not taking chances anymore in science, that we're sort of doing the old boring stuff, and I think there's some truth to that, so I think we need some new ideas to get people's attention’.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,103
Score d'incertitude au seuil0,303

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,026
Tête enseignante GPT0,320
Écart entre enseignants0,294 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2023
Routes d'admission2
Résumé présentoui

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