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Record W1989554781 · doi:10.4138/atlgeol.2014.008

Till geochemical signatures associated with the Sisson W-Mo deposit, New Brunswick, Canada

2014· article· en· W1989554781 on OpenAlexaffvenueabout
Beth McClenaghan, Allen A. Seaman, Michael A. Parkhill, Antonius Pronk

Bibliographic record

VenueAtlantic Geology · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsGeological Survey of Canada
Fundersnot available
KeywordsGeologyGlacial periodGeochemistryGlacierMineralogyGeomorphology

Abstract

fetched live from OpenAlex

A till composition study was carried out around the Sisson W-Mo deposit, New Brunswick, Canada, one of the largest W deposits in the world, to test modern analytical methods for W in till and document glacial dispersal from a significant W source. The <0.063 mm fraction of till defines glacial dispersal down ice of the deposit and use of this fraction is recommended for W-Mo exploration in the region. Metal-rich till overlying the deposit contains up to 816 ppm W and 63 ppm Mo. One km down ice, till contains 75 ppm W and 8 ppm Mo, and till in background areas contains a maximum of 7 ppm W, and 2 ppm Mo. Indicator elements for the deposit include W and Mo, and pathfinder elements include Ag, As, Bi, Cd, Cu, In, Pb, Te, and Zn. This list of elements is more extensive than previously identified for the Sisson deposit or identified in other published till geochemical studies because of the polymetallic nature of the Sisson deposit and the broad suite of elements that can now be determined using modern analytical techniques. Lithium meta/tetraborate fusion inductively coupled plasma-mass spectrometry was used to determine the total concentration of W in till and is a fast and cost effective method as compared to those reported in the older literature. Glacial dispersal of W and Mo from the Sisson deposit is detectable at a regional scale at least 14 km down ice (southeast) using surface till sampling. A 2 km till sample spacing should be sufficient to detect glacial dispersal from a W-Mo deposit of this size.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.093
Threshold uncertainty score0.910

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.004
GPT teacher head0.172
Teacher spread0.169 · 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 teacher head, 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

Citations7
Published2014
Admission routes3
Has abstractyes

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