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Record W2286110020 · doi:10.14288/1.0052858

Mineral exploration of the Nechako plateau, Central British Columbia, using lake sediment geochemistry

2010· article· en· W2286110020 on OpenAlexaboutno aff
S.J. Hoffman

Bibliographic record

VenuecIRcle (University of British Columbia) · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyPlateau (mathematics)SedimentGeochemistryMineral explorationMineralHydrology (agriculture)Mining engineeringGeomorphology

Abstract

fetched live from OpenAlex

A lake sediment geochemical survey was undertaken over the Nechako plateau, central British Columbia, to test applicability of lake sediment sampling to regional exploration. Organic-rich samples were collected near the centres of approximately 500 lakes on a helicopter-assisted survey covering some 16,000 km². It was found that lakes overlying each of five major lithologies contain distinctive suites of trace metals, and that regional variations of Cu, Mo, Pb, Zn, Ni, Cr, Sr, Ba, Ag, Co, V, and Ga are related to differences in underlying geology, whereas anomalous levels of Cu, Mo, Pb, and Zn reflect mineralized bedrock or rock types favourable to the occurrence of sulphide concentrations. Possible mechanisms of anomaly generation were examined by detailed studies of the Capoose Lake Cu-Mo-Pb-Zn anomaly, and the Fish and Portnoy Lake Cu-Mo anomalies, both previously defined by the regional survey. Capoose Lake, a large cligotrophic lake, occupies a 'U'-shaped valley, and is characterized by Fe- and Mn-rich and organic-poor sediment. In contrast. Fish and Portnoy Lakes are small dystrophic and eutrophic ponds, respectively, completely surrounded by bogs. They contain organic-rich and Fe- and Mn-poor sediment. These studies show that anomalous accumulation of Cu, Zn, and Mo in soils, streams, and lakes reflects weathering of sulphide occurrences. Cu, Zn, Mo, Fe, and Mn concentrations associated with chemical phases comprising overburden materials were partitioned using partial extraction experiments. Cu, Zn, and Mo anomalies in soils reflecting mineral occurrences are commonly hydromorphic, although anomalies formed by mechanical processes are prominent near bedrock exposures. Cu and Zn are more firmly bound in soils and stream sediments than lake sediments, with the proportion of these elements associated with (and presumably scavenged by) amorphous Fe oxides increasing from soils to stream sediments to lake sediments. Mo is held by both amorphous and crystalline Fe oxides. An increase in the scavenging ability of amorphous Fe oxides from soils to streams sediments also is observed in the Fish and Portnoy Lakes area. However the bulk of the Cu, Zn, and Mo in the latter two lakes is apparently bound to organic matter. Metal levels within lake sediments are highly variable, and within each lake the maximum range of concentrations commonly exceeds an order of magnitude. Zones of greatest Cu, Zn, and Bo enrichment are within 10 to 150 m from shore, downslope from mineral occurrences. Metal accumulation favours zones slightly above the base of the nearshore slope, where the volume of emerging groundwater presumably is greatest. Anomalies are also generated by inputs of metal-rich fines carried by streams. Consequently for maximum anomaly contrast, samples should be collected from zones where dissolved metals or metal-rich silt and clay are flowing into a lake. Coarse clastic sediment should be avoided.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.161
Teacher spread0.150 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2010
Admission routes1
Has abstractyes

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