Field And Experimental Tainting Of Arctic Freshwater Fish By Crude And Refined Petroleum Products
Notice bibliographique
Résumé
We have investigated two incidence of tainting of fish from northern Canada: one by effluent spilled born a synthetic crude oil production plant on the Athabasca river in northern Alberta, and one by diesel fuel spilled when a truck overturned near the Cameron River, Northwest Territories. These cases resulted in complaints that whitefish taken downstream fiorn the spill sites became tainted. Supplies of the spilled materials were available, and laboratory tests confined the ability of the spilled materials to produce oily taints in fish. These confirmatory experiments lead to a more systematic study of the relationship between exposure of fish to oil in water and tainting as judged by the responses of taste panels, Fish (rainbow trout and arctic char) were exposed experimentally to three mixtures of Norman Wells oil (nominally 3, 12 and 50 ppm) in water over a period of seventy-two hours. Fish were then transfemed to clean holding tanks where they were held for a fhrther 600-840 hours. Three fish were removed from each tank at intervals over both uptake and clearance phases in order to measure the production and subsequent loss of the oily taste. Taste panel members were selected for their ability to detect, identi~ and rank correctly weak mixtures of oil in water. All panelists were able to discriminate between treated and untreated fish during the uptake phase (mostly by the earliest sampling period of four hours) and early clearance phases. Panelists continued to detect taint in the fish at the end of the clearance phase of the experiment (600 and 840 hours), The implication of these taste panel results is that oil tainting is sensitive to the concentration of oil, the duration of exposure, and duration of the clearance phase. Rainbow trout and arctic char can be expected to become tainted after an exposure of only a few hours and to remain tainted for a month or even longer, following removal to clean water. © 2002 WIT Press, Ashurst Lodge, Southampton, SO40 7AA, UK. All rights reserved. Web: www.witpress.com Email witpress@witpress.com Paper from: Oil and Hydrocarbon Spills III, CA Brebbia (Editor). ISBN 1-85312-922-4
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 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 ».