Past Experience from Arctic Commercial Expeditions
Notice bibliographique
Résumé
In the past, Norwegian vessels have entered the Arctic for fishing and for hunting whales and seals. The seal hunters needed to go to the iceedge or into the ice to catch the seals and their activity created much needed income in the past. These seal hunters came mainly from the Aalesund area of Norway (many came from the village of Brandal) and from the Tromsø area in the north. Although seal hunting is controversial to day, there might be important learning to bring to new industries like the offshore oil and gas industry and to the navigators in ice infested northern waters. An activity within the research project “PetroArctic” at NTNU has focused on collecting experience data from the seal hunters, (Alme, 2009). A number of interviews with elders (age from 70 to 80+) have been conducted with focus on the physical environmental conditions, vessel behavior in ice and causes of loss of vessels. Among those interviewed were the legendary captain Paul Stark who sailed on sealers from 1950 to 2000 and who was involved in three vessel losses. Newspaper records from the early decades of the 20th century have been reviewed. Prior to the time of steel hull ships with diesel engines, wooden ships with sails and thereafter with steam engines were used. There were frequent losses caused by ice pressure and vessel implosions. Losses were also due to interaction with “ice foots” (Figure1) of multiyear ridges or due to hits from floating ridges on waves. The paper presents characteristic features of vessels used and ice conditions for the different areas where seal hunting took place. These were the Newfoundland area, Labrador coast, Danish Strait, the Area in vicinity of Jan Mayen, North East Greenland coast, Spitzbergen, Eastern Barents Sea towards Novaya Zemlya and the mouth of the White Sea (Figure 2). The causes for the losses or damages to vessels are reviewed in details. In this respect it should be noted that although the ice cap might be shrinking in the future, there will be ice parts of the year over large areas. The ice might even move faster than in the past and get to new areas that traditionally have been ice free. This also relate to the ice of the polar pack that might move more than in the past. There is therefore a strong encouragement to implement the learning of the Arctic pioneers.
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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,006 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,002 |
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 ».