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Enregistrement W2326949229 · doi:10.1093/ae/60.3.192

Bringing up the Rearing

2014· article· en· W2326949229 sur OpenAlexaboutno aff
John Acorn

Notice bibliographique

RevueAmerican Entomologist · 2014
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiquePlant and animal studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGeography

Résumé

récupéré en direct d'OpenAlex

It is now mid-August and I have to admit, I’m feeling a bit empty. I just realized that I haven’t reared a single insect this year, and I miss it. Usually, I’ll encounter a larva or pupa that I don’t recognize, and “rear it out” in order to make identification easier. Either that, or I will purposely obtain eggs or larvae as part of some other project. But this year, at least so far, I’m more or less grubless. I realize that for some entomologists, rearing is part of the job, and if you are one of those people who rear thousands of insects, day in and day out, perhaps my perspective will seem peculiar, but for me, rearing is merely an occasional and an enjoyable part of being an entomophile. I like the nurturing aspect of rearing, and I find that it is a perfectly good replacement for gardening, in which I seem to have no interest at all. Rearing caterpillars is especially enjoyable, perhaps because caterpillars are among the best-looking of immature insects. I only realized this fact when I started writing this column, but it should have been obvious, thinking about the larvae of, for example, flies, beetles, and hymenopterans. They are all quite fascinating, but generally not crowd-pleasing, while most caterpillars are colorful, appealingly shaped, and cute. I guess it makes sense—larvae need to grow, so they need a softer exoskeleton than the adults, and unless they also possess protective coloration or setae, they wind up looking pale and grub-like. I give butterflies a great deal of my attention, but most of my caterpillar-rearing experiences have been with the larvae of moths. Either way, I enjoy it. The combination of peaceful, attractive larvae and fresh-cut plants for food (so long as you keep things clean, and avoid a disgusting layer of moldy frass on the cage bottom) makes for an aesthetically pleasing daily routine. Caterpillars do need daily care, and many of my lepidopterist friends have lamented that they couldn’t travel much during the summer because they had caterpillars to look after. It’s a lot like having a puppy, or two, or three. I think the most amusing stories involve people who decide to go into the field on collecting trips, and take all of their rearing cages with them, in the back of the vehicle. Kids like caterpillars too, and the rearing of butterflies (painted ladies and monarchs, generally) is a part of the curriculum for many students. It has resulted in a bit of a controversy over whether these reared butterflies cloud our understanding of butterfly migration, but it is certainly a big hit in the classroom. My son Jesse was extremely keen on caterpillars when he was in his pre-teens, and we always had a cage or two to look after during the summer months, as well as some trays of pupae in the fridge over the winter. Usually, we would wait for a particularly nice female moth to show up in the light trap, and then see if she would lay eggs in a paper bag. In some places (for example, Japan and eastern Europe), beetle rearing is not far behind caterpillar rearing in popularity, but not here in North America, where we don’t allow such things, at least with “exotics.” Many years ago, when I was able to get a federal permit to rear tropical scarab beetles (I focused on goliathines), I learned a great deal, had marvelous living creatures to show to my undergrad students, and was able to supplement the offerings at the local insect zoo at the Royal Alberta Museum. I miss those days. Jesse used to help me scrub the mites off the grubs’ mouthparts, holding them with one hand, under warm tap water, and scrubbing with a soft toothbrush with the other.

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)0,002
score de la tête « metaresearch » (Gemma)0,007
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
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 enseignants0,356
Score d'incertitude au seuil0,918

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,007
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0010,001
Études des sciences et des technologies0,0080,001
Communication savante0,0050,006
Science ouverte0,0030,011
Intégrité de la recherche0,0040,009
Charge utile insuffisante (le modèle a refusé de juger)0,3560,228

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 Opus0,035
Tête enseignante GPT0,218
Écart entre enseignants0,183 · 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.

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

Citations1
Publié2014
Routes d'admission1
Résumé présentoui

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