The use of property-scale portable X-ray fluorescence data in gold exploration: advantages and limitations
Notice bibliographique
Résumé
This study examines field portable X-ray fluorescence (pXRF) data for unsieved B- and C-horizon soil samples from two contrasting Au exploration programs in northern Canada and compares them to laboratory results from sieved samples to determine if a minimalist approach to sample preparation, equipment calibration and analysis produces results that are adequate for exploration purposes. The collection of 14 651 residual soil samples on detailed grids at the Whiskey Au project in the Black Hills of the Yukon Territory, Canada during the 2011 field season allows a comparison of pXRF data from unsieved samples with inductively-coupled plasma mass spectrometry (ICP-MS) data from the <100-µm grain size fraction digested in aqua regia. XRF data were generated on two devices: an Innov-X Delta handheld and a Niton FXL desk-top unit. Data for selected elements from the pXRF units show trends in gridded percentile plots comparable to the ICP-MS data, although the continuity of these trends reflects the degree to which the pathfinder element concentrations exceed the lower orders of detection. Acceptable merged gridded images for As and Cu from the two devices were generated without data levelling, whereas the Pb, Mo and Ni data require leveling prior to gridding in order to provide a reasonable fit to the laboratory data. Data for elements that occur in concentrations close to the lower limit of detection by pXRF, such as Sb, may provide some useful information but must be used with caution. Data for Fe also show a poor correlation, possibly due to heterogeneity of Fe in the samples, as well as due to incomplete digestion of all Fe-bearing minerals in some samples using an aqua regia digestion. A total of 680 till samples collected from regional and detailed sampling grids on the Kiyuk Lake Au property in southern Nunavut, Canada during the 2012 field season were analysed by pXRF and also by ICP-MS following an aqua regia digestion. pXRF data were generated on an Innov-X Delta using unsieved samples for comparison with ICP-MS data from the <70-µm grain size fraction. The pathfinder element As shows good agreement with the laboratory data, whereas Ni, Mo and Sb data give poor matches due to proximity of the data to the lower orders of detection by pXRF. The use of pXRF data on soil samples with no sample preparation other than drying and no instrument calibration is a robust approach for Au exploration using particular elements, such As and Cu, provided the data are monitored for consistency. Even greater compatibility between pXRF and laboratory data would be expected where sample preparation and site-specific calibrations are implemented. Other pathfinder elements for Au, including W, Sb, Bi, Ag and Te, as well as Au itself, typically occur at levels in soil either close to or below the lower order of detection of the current generation of field-portable analytical devices. The use of pXRF in Au exploration allows for quick decision-making and provides near-real time sampling guidance in the field where ‘fit for purpose’ data for suitable pathfinder and lithologically-controlled elements can be obtained.
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 | 0,011 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».