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Enregistrement W4366602286 · doi:10.1002/tpg2.20344

Recipients of 2022 CSSA Editor's Citation for Excellence Named

2023· editorial· en· W4366602286 sur OpenAlexaboutno aff

Notice bibliographique

RevueThe Plant Genome · 2023
Typeeditorial
Langueen
DomaineDecision Sciences
ThématiqueAcademic Publishing and Open Access
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésExcellenceBiologyCitationComputational biologyLibrary scienceComputer sciencePolitical science

Résumé

récupéré en direct d'OpenAlex

The editorial board of The Plant Genome is pleased to announce the recipients of the 2022 Editor's Citation for Excellence. These awards recognize the outstanding professional commitment and dedication of volunteer reviewers and/or editors who, through their excellent insights and comments, have helped maintain the high standard and quality of papers published in the journal. Recipients were nominated based on their thorough, competent, and timely reviews or editing of manuscripts. Each will receive a certificate of appreciation, an ASA-CSSA-SSSA gift certificate, and recognition in CSA News. Dr. François Belzile was trained as a plant molecular geneticist and initially worked on DNA repair and recombination genes in the model plant Arabidopsis thaliana. Over the last 20 years, Dr. Belzile's lab at the Université Laval, Canada, has been interested in using genomics to develop novel approaches in plant breeding, mainly in soybean and barley. Dr. Belzile aims to act as a bridge and a facilitator between the lab-based genomic sciences and their numerous applications in the development of new and improved crop varieties. His lab works closely with industry partners to jointly develop and implement genomics-informed breeding programs. Dr. Rupesh Deshmukh is currently working as Associate Professor at the Central University of Haryana, India. He obtained his PhD degree in Agriculture Biotechnology from SRTMU, Nanded, India. His group is working on improving rice and tomato crops through integrated genomic approaches. Crop improvement for nutritive food and sustainable agriculture are two major areas of his research. His name is featured in a list of the World's Top 2% of highly cited researchers published by Stanford University. He received several highly competitive awards including Ramalingaswami Re-entry Fellowship and NASI-Scopus Young Scientist Award. He is recognized as a Fellow of the ISGPB and ARRW scientific societies. Dr. Humira Sonah earned her master's degree in Agriculture Biotechnology from Indira Gandhi Agriculture University, Raipur, India. She did her Doctorate from Banasthali University while working at the National Institute on Plant Biotechnology. Soon after her Ph.D., she joined Laval University, Canada, as a Postdoctoral Researcher where she was involved to explore the genotyping-by-sequencing method useful to accelerate crop improvement followed by Genome-wide association studies. She did another postdoctoral fellowship at Missouri University, USA. She rejoined Laval University and worked as a Visiting Professor. Considering her remarkable achievements in Plant Biology, the Department of Biotechnology (DBT), Government of India awarded her Ramalingaswami Fellowship which is one of the most prestigious awards aiming to attract high-quality Indian nationals working abroad. Presently, Dr. Sonah is Ramalingaswami Fellow at National Agri-Food Biotechnology Institute and her group is working to develop food-grade soybean. She was featured in 75 under 50, Scientist shaping today's India-2022 published by Vigyan Prasar, Government of India on National Science Day, and also featured in the list of world's top 2% researchers published by Stanford University (2022). Not pictured: Dr. Philipp Bayer, The University of Western Australia

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)0,014
score de la tête « metaresearch » (Gemma)0,045
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Science ouverte
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,032
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0140,045
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0060,001
Intégrité de la recherche0,0010,001
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 Opus0,095
Tête enseignante GPT0,379
Écart entre enseignants0,284 · 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.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

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
Publié2023
Routes d'admission1
Résumé présentoui

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