Geophysical strategies for kimberlite exploration in northern Canada
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".