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Enregistrement W3096166997 · doi:10.1002/fsh.10551

In Memoriam

2020· article· en· W3096166997 sur OpenAlexaboutno aff
Dick Beamish

Notice bibliographique

RevueFisheries · 2020
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueMarine and fisheries research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésWifeGovernment (linguistics)Fish <Actinopterygii>ManagementFisheryLibrary scienceSociologyPolitical scienceLawPhilosophyComputer science

Résumé

récupéré en direct d'OpenAlex

Donald James Noakes Many readers will know Don Noakes as the founding editor of Marine and Coastal Fisheries. Our fisheries science and management community lost Don on October 19, 2020 from complications associated with spinal cancer. He was only 65 years old and just retired in 2019. Don was proud to have graduated from the University of Waterloo as an engineer with expertise in applied time series modelling. He was equally proud to have been a student of Keith Hipel for both his master’s and doctoral degrees. Don arrived at the Pacific Biological Station immediately after receiving his PhD in 1985 and quickly became involved in a range of activities leading up to positions as head of aquaculture, head of Pacific salmon research, and then director from 1995 to 2003. Don left the Canadian federal government in 2003 to become dean of the School of Advanced Technologies and Mathematics as well as Associate Vice President of Research and Graduate Studies at Thompson Rivers University in Kamloops, British Columbia. After 11 years, he and his wife Olga wanted to return to Nanaimo, British Columbia, and in October 2014, he accepted the position as the dean of the Faculty of Science and Technology at Vancouver University in Nanaimo. Don Noakes had a diversity of talents with a solid background in applied mathematics. He was always available to help his colleagues with their analytical issues. He was an expert on the management of Pacific fisheries in general and Pacific salmon Oncorhynchus spp. and shellfish in particular, as identified by his publications. It was his analyses that helped convince colleagues, often for the first time, that climate changes and resulting impacts on ocean survival had become the major factors affecting Pacific salmon production. However, some of his most important contributions came from his research and advice to government and industry for the sustainable development of aquaculture on the Pacific coast of Canada. His skill in social science as well as a comprehensive analytical understanding of scientific issues made him a sought after communicator of science to the aquaculture industry and senior government officials. The aquaculture industry considered him a kind face at research meetings and workshops because of his thoughtfulness, his focus on evidence-based decision making, and his dry sense of humor. His last publication may be his most important. “Oceans of Opportunity: a Review of Canadian Aquaculture” was published in 2018 in Marine Economics and Management, volume 1, issue 1. In the paper, Don identifies the opportunities and challenges that are needed to use the ocean to produce seafood and provide employment, particularly in more remote locations along the West Coast. Some day there will be major coastal seafood farming industries stretching from Mexico to Canada to Alaska. It will be recognized that few scientists have contributed as much to the development of the marine aquaculture industry as Don Noakes. Don Noakes was a steady hand at the tiller with a wealth of insight and the odd pun. He was also a golfer, curler, photographer, gardener, barbecuer, candy maker, and his recent passion was the bagpipes. He was a proud member of the Kamloops Pipe Band, the Pacific Gael Pipe Band, and a supporter of all things Scottish. Most of all, Don Noakes was a true friend. Don will be remembered at a private family celebration and a larger gathering when pandemic restrictions are over. We send our condolences to his wife, Olga, his family, friends, and colleagues.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,030
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,208
Score d'incertitude au seuil0,697

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,030
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,001
Études des sciences et des technologies0,0040,001
Communication savante0,0080,005
Science ouverte0,0020,003
Intégrité de la recherche0,0040,009
Charge utile insuffisante (le modèle a refusé de juger)0,2080,145

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 Opus0,024
Tête enseignante GPT0,231
Écart entre enseignants0,208 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreAutre

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
Publié2020
Routes d'admission1
Résumé présentoui

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