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Enregistrement W2078327730 · doi:10.1063/1.2012477

Susan Caroline Bayliss

2005· article· en· W2078327730 sur OpenAlexaboutno aff
Andrei Sapelkin

Notice bibliographique

RevuePhysics Today · 2005
Typearticle
Langueen
DomaineNeuroscience
ThématiquePhotoreceptor and optogenetics research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésArt

Résumé

récupéré en direct d'OpenAlex

Susan Caroline Bayliss was due to join Queen Mary College, University of London, as a professor of nanotechnology. Sadly, she was involved in a fatal car accident near Manchester, UK, on 16 October 2004, just two weeks before she would have taken that position.Born in Ludlow, England, on 2 December 1954, Sue studied physics at King’s College London and graduated, with honors, in 1976 with a BSc. She worked for her PhD under Yao Liang at the University of Cambridge and submitted her thesis on symmetry dependence of optical transitions in layered materials. She obtained her doctorate in 1980 and remained in Cambridge as a research fellow at Lucy Cavendish College until 1985.For the next five years Sue was a postdoc at Leicester University, where among other things she used her expertise in optical spectroscopy to study light transmission through adult and neonatal eyelids in vivo for a local hospital. That ability to cross boundaries between disciplines had become the trademark of her research ever since. Sue then accepted a lectureship at Loughborough University; she remained there until 1994. During her tenure at Loughborough, she developed her close association with the Daresbury Laboratory synchrotron radiation source and applied a range of structural methods for materials research.Her research matured and she established her reputation as a capable scientist and original thinker at De Montfort University, where she accepted a job in 1994 as a senior lecturer. She worked in areas at the forefront of modern science: on combined structural and optical methods using synchrotron radiation under high pressure and on porous light-emitting silicon and bioelectronic systems. Her collaboration with biologists resulted in a series of pioneering publications on the interaction of nanostructured silicon with living neurons. In 1997 Sue was appointed a professor at De Montfort—and was one of the few female professors in physics in the UK at the time. She developed numerous links with researchers from Canada, France, Russia, Sweden, and the UK, which led to friendships and exchange trips. Her contributions to many areas of science were recognized: She was a member of several bodies that define the strategy of UK and European science and was an elected member of the European High Pressure Research Group Committee, an organization that promotes high-pressure research in Europe through annual meetings and awards. Sue shared her fascination with the properties of light through a series of lectures she delivered to local schools. Topics ranged from glowworms to luminescent nanostructures, and the series proved to be quite a success.An open-minded person who inspired her colleagues and students, Sue opposed fitting people into categories. Beyond science, she had a passion for sport and an ear for music. She played piano and flute, and sang in a rock band. An accomplished rower since her Cambridge years, she had fun racing rowing machines against men in a local gym, finishing first most of the time.Sue never stopped exploring. She was young in spirit and grasped life with all her heart. Her inner energy and unorthodox approach to life and science, best reflected in the following poem she wrote, provided an enviable example for those who came into contact with her: Susan Caroline Bayliss PPT|High resolution I can’t leave behind what I want toAll I can do is force a forgetAct indifferent and substituteSome of me, for embittermentBut enough. None will knowSo why should I be fretful?I have to do far too much nowTo waste time being reflectful.© 2005 American Institute of Physics.

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 enseignants0,111
Score d'incertitude au seuil0,966

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)0,0000,001

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 Opus0,053
Tête enseignante GPT0,328
Écart entre enseignants0,275 · 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

Citations0
Publié2005
Routes d'admission1
Résumé présentoui

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