An integrated assessment of potential granular aggregate resources in northern and southeastern Yukon based on seismic shothole drillers' logs and surficial geology maps
Notice bibliographique
Résumé
Granular aggregate (e.g., sand, gravel, boulders, and crushed bedrock) is critical to all manner of community, regional, and commercial infrastructure development including roads, airstrips, concrete production, petroleum well and building pads, and pipelines. Typically, granular aggregate is mined from glacial deposits such as eskers, kames, and sub- and pro-glacial meltwater channels; it can also be mined from modern or paleo-river deposits such as raised terraces. As the greatest economic cost of granular aggregate resources is typically associated with its transportation, and this cost increases exponentially with distance, undertakings that identify new potential sources in proximity to communities and prospective infrastructure development projects is regarded as being of particular benefit. This study uses drillersmp;gt;' logs from past seismic operations throughout northern and southeastern Yukon as a means of identifying potential surface and subsurface (buried) granular aggregate resources. During the auger drilling of seismic shotholes, drillers logged the earth materials they were drilling through at varying degrees of resolution and accuracy. Past success using seismic shothole drillersmp;gt;' logs to identify a large buried granular aggregate deposit in northeastern British Columbia has demonstrated the efficacy of this type of investigation (cf., Levson et al., 2004). Using a database of >275 000 archival shothole drillersmp;gt;' log records from Yukon and Northwest Territories (Smith and Lesk-Winfield, in press), this project has queried, sorted, and interpreted the data from which databases and shapefiles of mp;lt;"gravelmp;gt;" (including boulders and rocks), mp;lt;"gravel + sandmp;gt;" and mp;lt;"sandmp;gt;" deposits have been integrated into a regional Geographic Information System (GIS). Additionally, potential granular aggregate data from a geotechnical borehole database (Smith et al., 2005) and a separate database of seismic shothole drillersmp;gt;' logs from Yukonmp;gt;'s North Slope and Mackenzie Delta region (Côté et al., 2003) has been interpreted and integrated into the GIS. This publication also includes granular aggregate-associated surficial geology map polygons (e.g., glaciofluvial deposits, alluvial terraces) extracted from the recent digital compilation of Yukon surficial geology maps (Bond and Lipovsky, 2009), and a new potential granular aggregate assessment in the Peel River watershed (Kennedy, 2009). The benefit of including the map polygon data is that it can be used to confirm or question the identification of potential granular aggregate deposits from coincident shothole records. Furthermore, it can give a sense of the potential geographic extent of what is otherwise point-source shothole data. The GIS created by this project is designed to give the user a visual sense of the distribution and size of potential granular aggregate deposits, while at the same time providing the ability to search and query the actual records throughout the geographic extent of the data. In all cases, users are cautioned that seismic shothole-associated deposits identified in the GIS should only be considered mp;lt;"potentialmp;gt;" granular aggregate resources all deposits require field verification, as well as a proper assessment of their sedimentological and lithological characteristics prior to their engineering application, or inclusion as part of a regional resource inventory. Notwithstanding these limitations, past success in using this kind of information to prospect for granular aggregate resources, land the shear volume and geographical extent of new information provided by this project is likely to make this a particularly invaluable resource for Yukon.
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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 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 ».