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Record W2982039965 · doi:10.4095/296471

Identifying new vectors to hidden porphyry-style mineralisation

2015· report· en· W2982039965 on OpenAlexaffabout
N Rogers, A Plouffe, J B Chapman, M B McClenaghan, Dawn A. Kellett, Robert A. Anderson

Bibliographic record

Venuenot available
Typereport
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsGeologyGeochemistryMineralization (soil science)Mineral explorationIntrusionPorphyry copper depositDevonianHydrothermal circulationEarth sciencePaleontologyFluid inclusionsSoil scienceSoil water

Abstract

fetched live from OpenAlex

Intrusion related (e.g., porphyry) deposits are the most important sources for Cu, Mo, W and Sn, along with Au, Ag, and PGEs. Porphyry deposits are large, low- to medium-grade deposits in which mineralisation is hosted within and immediately surrounding distinctive intrusive phases within larger intrusive complexes that commonly have prolonged emplacement histories. To develop more effective exploration criteria to identify and evaluate deeply buried and/or hidden fertile intrusive mineralizing systems, studies into Cu-Mo/Au and W-Mo-Sn systems are aimed at answering the following questions: i) Are there distinctive proximal and distal footprints for each deposit type that will allow identification of, and vectoring towards hidden economic deposits?; ii) Is there evidence of fertility within the root system of intrusions, i.e. what are the triggering conditions and indicators of an hydrothermal-magmatic system of size and duration sufficient to develop a large porphyry deposit? To help answer these questions studies are being undertaken at sites associated with the Triassic-Jurassic porphyry deposits of the British Columbia interior and for the array of mineralised Canadian Appalachian Siluro-Devonian intrusions, for which the fundamental geoscience knowledge is often lacking. A common problem facing Cordilleran and Appalachian exploration is how to detect intrusion-related mineralization through the extensive glacial sediment cover. Consequently, research activities are focussing at identifying key geochemical and mineral indicators in till near known mineralization and their detrital dispersal down-ice. Indicators are being developed for the detection of mineralization, but also the alteration halos and vein systems associated with mineralization, which represent much larger exploration targets than the actual economic orebody itself. Once identified in till, these indicators can be traced to their bedrock source using reconstructed ice movement vectors. Structural relationships indicate that Sn-W-Mo mineralised intrusive systems can form due to extension associated with far removed non-orthogonal accretion. Deposits within these bodies form along fluid pathways such as the intersection of high-angle syntectonic breaks. Mineral potential can also be resolved through trace element fingerprinting. Subtle compositional changes in commonly occurring minerals (i.e., biotite) and fluid inclusions provide evidence of chemical variations related to magma fertility and vectors to mineralisation.

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)0.001
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 score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
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 head0.110
GPT teacher head0.314
Teacher spread0.204 · 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

Citations0
Published2015
Admission routes2
Has abstractyes

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