Application of Factor Analysis in the Identification of a Geochemical Signature of Buried Kimberlites in Near-surface Groundwaters in the Attawapiskat Area of the James Bay Lowlands of Northern Ontario, Canada
Notice bibliographique
Résumé
In the James Bay Lowlands of northern Ontario, kimberlite pipes are concealed by peat, thick layers of till, and Tyrell sea sediments. Studies have shown that buried ore bodies produce geochemical signatures in surface media. This thesis explores the geochemistry of near-surface groundwater above concealed kimberlite pipes using factor analysis to determine whether (1) a factor analysis can reveal an underlying structure (factors) in a multivariate groundwater geochemical dataset, and whether (2) those factors are related to the presence of concealed kimberlite. Factor analysis was performed on two datasets of nearsurface groundwater, collected at 0.2 m and 1.1 m below ground surface in peat. Results revealed that (1) there is a significant difference in the behaviour of elements in groundwater near the surface compared to those in deeper groundwater, which is sheltered from the effects of the atmosphere; (2) for both datasets, the first factor is dominated by elements known to be enriched in kimberlite, notably rare earth elements (REE), U, Th, Ti – the composition of factor one is consistent with their derivation from kimberlite in a limestone background where such elements are in very low concentration; (3) high-valence and lowvalence kimberlite indicator elements (KIE) are found separated into distinct factors suggesting that once released from the kimberlite after weathering, KIE are subjected to various geochemical processes to be differentiated as they migrate upward to the surface; and (4) Fe and Mn load on a factor distinct from other metals, suggesting that in this environment Fe-Mn-O-OH is not a significant controller of metal mobility in groundwater. Overall, this research has further highlighted the multivariate nature of geochemical processes in groundwater. Compared with previous work in geochemical exploration where often only univariate or bivariate statistics or single element profiles over concealed ore bodies were used, this thesis has shown that factor analysis, as a multivariate data analysis technique, is a robust exploration tool, able to shed light on relevant geochemical processes hidden within geochemical datasets. This thesis shows that high-valence KIE, notably U,V, Th, Ti and the REE, as a group, are better indicators of the presence of kimberlites than other well-known KIE. Single element concentration profiles such as Ni or Cr (known KIE) show similar anomalies over a concealed kimberlite as a factor score profile for factor one (U, V, Th, Ti, REE, Ni) would; however, it is the peculiar assemblage of elements in factor one that makes it unique to kimberlites, a feature that can be used in future exploration work for concealed kimberlites in similar surficial environments, such as the Siberian wetlands. The results suggest that future geochemical exploration work involving groundwater should focus on the more stable groundwater located below the zone of oxidation, sheltered from the effects of the atmosphere.
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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 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| 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 ».