Indicator mineral and till geochemical dispersal patterns associated with the Ranch Lake kimberlite, Lac de Gras region, NWT, Canada
Bibliographic record
Abstract
The Ranch Lake kimberlite, in the Contwoyto Lake area of the northwest Territories, consists of volcaniclastic crater facies kimberlite which contains thousands of kimberlite indicator mineral grains in a 10 kg sample. Cr-diopside and pyrope are the most abundant indicator minerals in the kimberlite, accompanied by much less abundant chromite and rare Mg-ilmenite. Indicator minerals in till samples collected around the Ranch Lake kimberlite define a spectacular ribbon-shaped glacial dispersal train trending west for 70 km. At its head, the train is 500 m wide and gradually widens 2 km at 20 km down-ice. The lateral edges of the train are sharply defined by the presence or absence of indicator minerals in till. Background (up-ice) concentrations of all indicator minerals are zero. Patterns for Cr-diopside and pyrope abundance are similar and concentrations increase down-ice, reaching their highest levels between 15 and 19 km down-ice. Of the two size fractions of heavy minerals examined, most indicator minerals occur in the finer, 0.25 to 0.5 mm, size fraction. The <0.063 mm fraction of the till matrix displays weak geochemical signatures of the kimberlite down-ice, most notably for Ba, Cr, Ce and Th. The results of this study of indicator mineral and geochemical methods around a known kimberlite will aid in the design of mineral exploration programs for kimberlite-hosted diamond deposits in glaciated terrain around the world.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".