Notice bibliographique
Résumé
Have you ever heard how quiet owls are when they fly? They are very stealthy, giving them a distinct advantage over their prey. Owls can also pick up sounds that are almost inaudible to the human ear while hunting. However, great gray owls (Strix nebulosa) live in cold environments, often with snow on the ground, which can make hunting by ear more difficult, because their prey, such as voles (Cricetidae), hide beneath the snow and the sounds they produce could be dampened by the icy covering. Christopher Clark from University of California, Riverside, USA, James Duncan from Discover Owls, Canada, and Robert Dougherty from University of Washington, USA, wanted to know how the sounds produced by prey are affected by the presence of snow and how the owl overcomes these acoustic challenges to hunt.First, the team wanted to find out how snow affects how sound carries. They went out into the field during the winter (February) in Manitoba, Canada, to identify locations where the owls had been hunting, and found seven holes in the snow produced by owls as they retrieved their food. Then, they dug 40 cm deep holes near the owls’ hunting sites and placed a waterproof loudspeaker at the bottom; they also placed an acoustic camera 1–1.5 m above the snowpack and 1.2–6 m from the loudspeaker. The team then played a recording of the sounds produced by a meadow vole (Microtus pennsylvanicus) digging beneath the snow through the loudspeaker, while gradually scraping the snow away in layers, recording the volume and location of the sound relative to the speaker at six snow depths. They used this information to simulate how the owl would perceive the sound after it traveled through the snow.They found that snow does in fact act as a muffler for sound produced by rodents buried beneath it, especially for high-pitched sounds, such as when the voles are communicating with one another. As the snow was removed, the sound level increased and the location of the sound also appeared to move, with the sound source appearing to be displaced farthest to one side of the speaker when the snow was deepest, moving closer to the speaker as the snow was removed until it appeared to come directly from the speaker when all the snow was gone. The team suggests that owls could overcome this challenge by positioning themselves well above the snow, either on a perch or flying high, to reduce the likelihood of being misled by the distorted sound position. And it seems that the great gray owls have already come to the same conclusion as they often hover directly above their prey before plunging into the snow, to increase their accuracy.The work done by Clark and colleagues highlights how the snow creates a sound illusion by bending the path of the sound – much like light is bent when passing through a glass of water, making a straw appear bent – directly affecting how great gray owls target food beneath snow cover. The birds have also evolved to fly extremely silently, diminishing the noise produced by their own flight, allowing them to overcome this sound illusion and hear voles digging beneath the snow while they hover above. One could say that these birds are the ninjas of the sky.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».