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Record W2185794671

Geophysical strategies for kimberlite exploration in northern Canada

2007· article· en· W2185794671 on OpenAlexaboutno aff
Aurora Geosciences Ltd

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsKimberliteDiatremeGeologyFaciesImpact craterGeophysicsSeismic refractionGeochemistryGeomorphologyStructural basinMantle (geology)
DOInot available

Abstract

fetched live from OpenAlex

Geophysical methods are a critical component of kimberlite exploration programs in northern Canada. Successful projects require the application of complementary techniques selected on the basis of the kimberlite facies likely present in the target area. Because of differential glacial abrasion, kimberlites may be eroded to different levels in a target area. The facies of kimberlite exposed in the scoured top of an eroded pipe will govern the geophysical response. In general, total magnetic field surveys are useful in locating pipes or dykes regardless of the kimberlite facies present. Crater facies kimberlite shows the greatest contrast in physical properties with respect to granitic and gneissic country rock and this facies of kimberlite responds well to electromagnet ic surveys. Unfortunately, surficial sediments can generate EM and magnetic field responses which resemble those of crater facies kimberlite. The critical problem in screening these anomalies is to determine whether the associated resistivity low persists to depth. Because the low resistivity material is also less dense tha n the surrounding rocks, gravity surveys, suitably corrected for the effect of the water column if conducted over lakes, can be a useful screening tool in this situation. Capacitive coupled resistivity (CCR) and seismic refraction surveys are also useful in determining the source geometry. Diatreme facies kimberlite produces more subtle responses than crater facies kimberlite and also generates anomalies easily confused with surficial features. For both crater and diatreme facies kimberlite pipes, ground penetrating radar (GPR) surveys can be used to define their tops and guide subsequent drill testing but are of limited use in conclusively identifying kimberlite in the absence of other methods. Hypabyssal kimberlite is most often found in dykes and sills and can be mapped with total magnetic field and investigated in detail with GPR or seismic reflection surveys.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.273

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 studies0.0050.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.016
GPT teacher head0.254
Teacher spread0.238 · 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

Citations8
Published2007
Admission routes1
Has abstractyes

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