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Enregistrement W2460992563 · doi:10.1002/bes2.1249

Unearthed! The Amazing Microbiome Exposed: The Established Researcher

2016· article· en· W2460992563 sur OpenAlexaffabout
John N. Klironomos

Notice bibliographique

RevueBulletin of the Ecological Society of America · 2016
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueMycorrhizal Fungi and Plant Interactions
Établissements canadiensUniversity of British Columbia, Okanagan CampusKelowna General HospitalUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésEcologyMicrobiomeBiologyMicrobial ecologySociology

Résumé

récupéré en direct d'OpenAlex

Most of us can identify a group of people that have influenced the direction of our careers and of our research programs. For me, a few individuals were pivotal at different stages of my research career. As an undergraduate student majoring in biology at Concordia University, my goal was to enter a medical profession rather than a career in ecology. That all changed in my final year when I was introduced to soil microbial ecology by Paul Widden. I was dazzled by the diversity of organisms that could be viewed under the microscope. I found it very interesting that we could observe only a small proportion of the organisms in the soil, for many of which we have no idea what they do. I was hooked. This was the beginning of my interest in research. With a thirst for better understanding the microbial world, I then joined Bryce Kendrick's laboratory as a graduate student to study mycology. My research focused on the ecology of mycorrhizal symbioses, but it was also a great environment for a broad training in mycology and an appreciation of the important roles of fungi as saprobes, pathogens, and mutualists. As a postdoc in Mike Allen's group in San Diego, I focused on the use and management of mycorrhizal fungi in landscape restoration and their responses to climate change. John Klironomos. Photo taken by Miranda Hart. My research up to this point was exciting, but there was one aspect to the work that I worried about: Most of the research was built on experiments with plants grown in mycorrhizal treatments and nonmycorrhizal (sterile) controls. Such an approach is powerful in evaluating the contributions of mycorrhizal fungi. However, it is also of limited relevance as the nonmycorrhizal state is not typically found for most plants in nature. Nonetheless, this was (and still is) a standard method for studying mycorrhizal symbioses by many research groups. In 1997, a big change happened in my approach to studying plant–microbe interactions. While attending the Mycological Society of America meeting in Montreal, I listened to Jim Bever talk about a simple but powerful framework on plant–soil feedback. He showed how his concept could be used to study plant and microbial effects and responses at the same time. The approach was particularly attractive because it integrated soil microbes into dynamical frameworks of plant populations, which was novel at that time. The associated methodology was simple experimentation and had no requirement for nonmycorrhizal controls. Jim and his colleagues published their discoveries in a seminal paper (Bever, J. D., K. M. Westover, and J. Antonovics. 1997. Incorporating the soil community into plant population dynamics: the utility of the feedback approach. Journal of Ecology 85:561–573). Over the following decade, the framework by Jim and his colleagues led to an explosion of research studies on topics such as population and community dynamics, multitrophic interactions, determinants of rarity and invasiveness, climate change impacts, conservation biology, and landscape reclamation, among others. In reflecting on the contribution by Jim and his colleagues and the resulting impact on my research and the entire field, I believe there lies an important lesson. Many argue that advances in soil ecology are limited by available techniques. I certainly believe this; for example, our ability to better understand the identity and functioning of soil microbes has been vastly improved with recent advances in genomic techniques. However, conceptual/theoretical contributions may be just as influential, if not more so. Jim and his colleagues were able to stretch the field of soil ecology in a way that has resulted in more powerful questions, which are leading to research studies designed to provide more profound insight.

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)0,009
score de la tête « metaresearch » (Gemma)0,034
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,027
Score d'incertitude au seuil0,089

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0090,034
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,001
Études des sciences et des technologies0,0090,006
Communication savante0,0120,015
Science ouverte0,0010,011
Intégrité de la recherche0,0050,015
Charge utile insuffisante (le modèle a refusé de juger)0,0270,017

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 Opus0,017
Tête enseignante GPT0,211
Écart entre enseignants0,194 · 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'étudeObservationnel
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
Publié2016
Routes d'admission2
Résumé présentoui

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