Notice bibliographique
Résumé
In the summer of 1972, Chuck Racine, a young plant ecologist from Duke University, came to Alaska and found his calling studying the Arctic tundra.The discovery of oil at Prudhoe Bay, Alaska, in 1968, and the signing into law of the Alaska Native Claim Settlement Act (ANCSA) in 1971, cleared the way for one of the greatest acts of land conservation in history: the Alaska National Interest Lands Conservation Act (ANILCA).As part of the run-up to this conservation legislation, federal agencies began inventorying and assessing almost 100 million acres of Arctic and sub-Arctic lands in 1972, anticipating the creation of new national parks, wildlife refuges, and designated wild and scenic rivers.During that first summer, Chuck was recruited to serve on a 10-person team that evaluated lands on the Seward Peninsula for potential inclusion in the National Park system.Their evaluation study led to the creation of the Bering Land Bridge National Preserve.For the following four summers, Chuck continued in the same type of work, producing vegetation and floristic inventories of some of the most iconic lands in Alaska.During those years, he spent each summer in the field and each winter in the Lower 48 (mostly Vermont) writing up his results.Between 1972 and 1979 he authored nearly a dozen internal reports that contributed directly to the creation or expansion of the Bering Land Bridge National Preserve, Kobuk Valley National Park, Lake Clark and Katmai National Parks and Preserves, and Yukon-Charley National Preserve.A careful and meticulous observer, Chuck also began to notice and record the impact of fire and human disturbance on tundra during these long summer seasons.This was how he became a pioneer in this branch of ecology, and it became the focus of four decades of research.In the end, he published 65 widely recognized papers, six of which appeared in this journal, and he helped set the pattern for how this type of research should be conducted.Chuck was born on 22 May 1940 and grew up in Hinsdale, Illinois.He attended Lake Forest Academy in Illinois, then Dartmouth College, where his interest in plant ecology began.But it was during his graduate education at Duke University that he first became aware of the possibilities of the Arctic.His PhD began under the direction of H.J. Oosting, but when Oosting passed away, W.D. Billings took Chuck on as a student.Billings has been called the "father of Arctic plant ecology" and before long Chuck was headed north.In 1969, he completed his dissertation on the community dynamics of the oak forests of the southern Blue Ridge Escarpment.He spent the next two field seasons in the Galapagos Islands studying plant-animal interactions, but as fate would have it, in 1972 his opportunity arrived, and from then until his death in 2014, his passion was the tundra.During those years, he held academic positions at Ohio State University, Notre Dame, North Carolina State University (where he met his wife Marilyn), and the Center for Northern Studies in Vermont, before becoming a research ecologist in 1987 at the U.S. Army Cold Regions
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,004 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,061 | 0,016 |
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 ».