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Enregistrement W2461401400 · doi:10.1242/jeb.112607

Dateless bees wear better perfume

2015· article· en· W2461401400 sur OpenAlexaff
Katie E. Marshall

Notice bibliographique

RevueJournal of Experimental Biology · 2015
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiquePlant and animal studies
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésMatingSet (abstract data type)Mate choiceBiologyEcologyZoologyComputer science

Résumé

récupéré en direct d'OpenAlex

Attracting a mate is an expensive endeavour – there are dances to learn, the right outfits to wear and an entire array of vocalizations to perfect. Because males are usually the sex that does the searching, most scientists have focused on the costs that they bear. But in a few species conditions can arise that cause females to invest in finding a mate. In these situations, females have to balance several costs: the potential cost of not producing any offspring if she fails to find a mate, the cost of mating itself and the cost of signalling to attract a mate.To best balance these costs, theory predicts that females should increase their signalling effort the longer that they spend without a mate, as the potential cost of failing to find a mate increases. Leigh Simmons, a researcher from the University of Western Australia, decided to test this hypothesis using the solitary ground-nesting Dawson's bee. As males only search for females immediately after the females emerge as adults, females who get left out during the first pass must find ways later to attract the attention of males by using a particular blend of chemicals found on their cuticles that function as a pheromone perfume. Would females that had failed to mate the first time round invest more in the chemical composition of their cuticle chemicals to attract a male on the rebound?First, Simmons nabbed 50 female bees right as they emerged from their burrows. He froze one set immediately, then isolated another set in a sort of bee nunnery away from males for a day and then froze them. Finally, he unleashed the remaining females to a group of male bees, allowing some to mate and perform their post-copulatory courtship behaviour, while others only mated (to isolate the effects of insemination on cuticle chemistry); and a final group was allowed to mate and nest after. This gave him five groups across which to compare the composition of their cuticle covering: one that was young and unmated, another that was older and unmated, one that had mated but not had post-copulatory courtship, one that had mated and had post-copulatory courtship, and one that was allowed to have all the normal mating behaviours and then nest afterwards. Simmons then used hexane to dissolve the chemicals from the cuticle of each bee before using gas chromatography to identify and quantify each chemical.He found a total of 21 compounds that dissolved out of the female bees’ cuticles, and the composition of the cuticle chemicals extracted from the female bees that had been unmated for a day had altered significantly. Meanwhile, the cuticle components of the bees that had mated (either with or without post-copulatory courtship) were more like those of the freshly emerged bees, and the chemical composition of the nesting bees’ cuticles differed from that of all of the other groups. So, the unmated female bees had altered the composition of their cuticle chemicals, while mated female bees did not.Not a lot is known about the costs of pheromone signalling or the mechanisms by which females can change their signalling, but in desperate times, it seems that at least female Dawson's bees break out their best perfume to find that lucky guy.

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)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut 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 enseignants0,019
Score d'incertitude au seuil0,063

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,000
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0190,006

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 Opus0,084
Tête enseignante GPT0,276
Écart entre enseignants0,192 · 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'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
Publié2015
Routes d'admission1
Résumé présentoui

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