Notice bibliographique
Résumé
59 HEIDI DIEHL WEISSHORN I n the hotel’s dining room, a glass punch bowl of pink yogurt sat higher than everything else on the table, pedestaled above cornflakes and muesli, small sausages, cheese rinded with what looked like shreds of grass. Coffee asserted itself. There were croissants lined up and rolls in a basket. I didn’t know where to begin. “There she is.” My mother was suddenly beside me, her face radiant. Her long gray hair was wrapped in a bun above her turtleneck. For years, she’d refused to cut her hair short; she didn’t want to look like an old lady. Until this trip, I hadn’t thought of her that way—she was seventy-two, but still working as an archivist, still hiking and taking tai chi classes at the Y. But when I hugged her beside the yogurt, she felt insubstantial in my arms, her shoulders narrow, folding together. “We thought you would be here yesterday evening,” she said. I was joining my mother and her husband Werner’s family in the Alps to celebrate Werner’s seventy-fifth birthday. The trip from New York, on two flights and three trains, had taken me over twenty-four hours. “An old man started having breathing problems on the plane. We had to land on an airstrip in Newfoundland.” I’d been delayed by the emergency landing; my late arrival in Zurich made me miss my train connections, and I’d finally gone up into the mountains in complete darkness. I made it to the hotel after midnight, and I hadn’t been able to tell anyone this story yet. “They didn’t give us any information—just told us to fasten our seatbelts. I thought we were going down in the ocean.” “Come and see everyone, Nina,” my mother said. She linked her arm through mine and led me to a round table beside huge windows. The view was stunning—mountains beyond the green and white of fir trees and snow, everything perfect through the glass. colorado review 60 Werner stood up to greet me. “I’m sorry I was so late,” I said as I embraced him. “I hope you weren’t worried.” “Oh, no,” Werner said with his usual briskness. “We knew you’d show up. Here is Ulf.” Werner motioned to his tanned and well-preserved brother, who greeted me warmly, though I’d met him only a handful of times, the first when my mother married Werner on a festive night twelve years ago. The brothers were Swiss, though Werner had lived in the u.s. for thirty years, studying caribou migration and teaching wildlife biology. Werner continued his introductions. “Rudi and Elke,” he said, motioning to a couple around my age wearing matching fleece vests—Werner’s son and his wife. They lived in Basel and worked for Ulf. I’d never met Elke, and I barely knew Rudi. He squeezed my hand. He didn’t look like Werner, who was wiry, who’d been dark-haired before his beard turned white. Rudi was strapping and blond, with the shaggy affability of a golden retriever. I returned to the breakfast spread and filled a small plate, avoiding the strange cold cuts, gravitating toward the cheese. Back at the table, I sat next to my mother. “Our latest American representative,” Rudi said to me. He cut his roll with a knife and fork. “What do you think of our mountains?” “I’m glad to see them in daylight,” I said. “How is the view?” Elke asked. Her crisp accent made her question almost accusatory. “Did you see the Weisshorn?” She buttered a croissant, which seemed like overkill to me. “It’s beautiful.” I’d seen many mountains—one of them must have been the Weisshorn. “I looked at it from my bed this morning .” “For me, the same. I awoke to something gorgeous, and I’m I wanted to talk to my mother , to see if I could notice any differences. She seemed to be listening with her usual sharp focus, but I was afraid of what I might see if I looked closely. } 61 Diehl not referring to my...
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) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,006 | 0,003 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,608 | 0,440 |
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 ».