Notice bibliographique
Résumé
CENTRAL OKLAHOMA Margaret Morae Nice. In 1919 the best place to study birds near Our home was along Snail Brook, a sluggish little stream just west of Norman. On one of my visits in December I decided to make a special study of the most convenient stret~h, which I called the First Half Mile. At that time this tractt was a woods in miniature with primeval trees, a great deal of undergrowth, weeds, a cre~k and a small pond. bordered by a few acres of unbroken prairie and cultivated fields; at all seasons, cover, food and water were present in abundance. Hence this portion of Snail Brook was attractive at all times of the year and to a wide variety of birds. Moreover, it was comparatively isolattd, yet not too much; to the north, west and east there was no cover at all; but to the south the Second, Third and Fourth Half Miles stretching nearly to the woods by the South Canadian river, formed, with their trees and thi~kets, a natural avenue for many birds to travel up and down. For three years I carried out almost weekly censuses of the birds on the area selected, but by 1922 the region was becoming greatly injured through the inroad9 of civihzation. The pond had been drained in the spring of 1921 and a small houst' built on the prairie; the vegetation was not disturbed until the summer of 1922 when considerable cutting of trees and shrubbery took place. .After this more houses w~re built, more clearing dpne, while the best woods left was turned into a hog pasture, therefore in 1923 and 1924 I ceased my l'isits almost entirely. vVe were away from Norman from June 1924 to September 1925; on our return I found Snail Brook had regained some of its lost prestige, since the hogs had gone and their former home was a wilderness of weeds. Consequently I took up the study again. From December 1919 to Decembe. 1926 I made 210 censuses and 90 vishs; on a census I went along the ~tream the whole half mile recording every bird I saw, an a visit 1 only went partway. Since the trees and bushes merely borrlered the creek, it was possible to get fairly accurate counts as 10:Jg as the leaves were off; late spring, summer and early fall censuses were less accurate than the others. In December 1919 I made 2 censuses
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
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 tête enseignante, 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 ».