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Enregistrement W165088680

Giant Pandas: Biology, Veterinary Medicine, and Management

2007· article· en· W165088680 sur OpenAlexaboutno aff
Graham J. Crawshaw

Notice bibliographique

RevuePubMed Central · 2007
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueGenetic and phenotypic traits in livestock
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésIUCN Red ListCaptive breedingEndangered speciesAiluropoda melanoleucaThreatened speciesZoologyConservation biologyBiologyHabitatEcology
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The giant panda, probably the most recognizable of any species of wild animal, is seriously threatened in its native habitat in China. Pandas exist in zoos and in reserves in China but only a small number have ever been seen in Europe or North America. Studying such an elusive and rare creature in its mountainous habitat is a difficult task, but the opportunity to increase knowledge of the biology of the animal can be gained by studying animals in breeding centers and zoos. There is a paucity of well-documented reports in English of medical data and the diseases that affect giant pandas. From 1998 to 2000, teams of biologists, veterinarians, reproductive specialists and geneticists, under the umbrella of the Conservation Breeding Specialist Group of the IUCN-World Conservation Union, undertook an intensive study of more than 60 captive pandas in collaboration with animal managers and scientific colleagues from conservation and research centers in China. This book represents the result of those examinations combined with data collected from other studies of both captive and free-living animals. This is an exceptional publication presenting a wealth of current knowledge on giant panda biology, including health, behavior, reproductive physiology, genetics, and species management. Although taxonomically a bear, the giant panda demonstrates many features not typical of other bears, in particular those related to its unusual diet. The 22 chapters cover topics such as genetics, social behavior, nutrition, clinical findings, clinicopathological data, diseases and pathology, and the results of ultrasonographic, gastroscopic, and colonoscopic examinations. Several sections are devoted to reproduction, including normal reproductive physiology and endocrinology, as well as assisted reproductive techniques. For many years successful reproduction of captive pandas was a rare event — females are sexually receptive for just 3 days a year, and this, coupled with issues of incompatibility between prospective pairs, meant few giant panda births. However, knowledge of panda reproduction has increased greatly in the past decade resulting in a dramatic increase in the number of panda cubs now being born and surviving. Artificial insemination has resulted in live births, while artificial rearing and switching cubs has enabled panda keepers to raise rejected neonates, as well as twins when typically only one of a pair would survive. Much of this progress has been made by the Chinese themselves, but the techniques and their precision have been refined with the assistance of veterinarians and scientists from outside the country. The book, which is written and edited very well, includes the results of the survey in detail, along with data tables, photographs and up-to-date reference lists. As more giant pandas become available for study, further knowledge on their biology and medicine will be gained, including perhaps the cause of their various digestive diseases, and a stunting syndrome that was recognized in 15% of the pandas examined. While this book may be of limited interest to most Canadian veterinarians, it is essential reading for those seeking information on the medical care, reproduction, and other aspects of the biology of this appealing animal. It also demonstrates the tremendous rewards to be gained from multidisciplinary and multinational projects despite considerable political, logistical, and linguistic challenges, as well as the importance of documenting procedures in new species.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut 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: Empirique
Score de désaccord entre enseignants0,760
Score d'incertitude au seuil0,417

Scores Codex et Gemma par catégorie

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

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 Opus0,019
Tête enseignante GPT0,256
Écart entre enseignants0,237 · 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 tête enseignante, 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

Citations4
Publié2007
Routes d'admission1
Résumé présentoui

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