Kimberlite indicator mineral chemistry of the Bucke and Gravel kimberlites and associated indicator minerals in till, Lake Timiskaming, Ontario
Bibliographic record
Abstract
A well documented glacial dispersal fan of kimberlite indicator minerals extends southward from the region of the Late Jurassic Bucke and Gravel kimberlites in the Lake Timiskaming kimberlite field of northeastern Ontario. The Geological Survey of Canada collected and analyzed a sample of kimberlite from both pipes and re-examined and analyzed indicator minerals from archived heavy mineral concentrates of till samples from the dispersal fan. The Bucke kimberlite contains more than 30,000 indicator mineral grains per 10 kg sample in the 0.25 to 0.5 mm fraction, which consists of, in decreasing order of abundance, Crpyrope>> Mg-ilmenite>chromite>Cr-diopside. The Gravel kimberlite is three times as indicator mineral rich, containing more than 100,000 grains per 10 kg sample in the 0.25 to 0.5 mm fraction, which consist of Mg-ilmenite>>Cr-pyrope>chromite>Cr-diopside. No olivine was recovered from either sample. Till samples within the fan contain 100s to 1000s of indicator minerals per 10 kg sample, mostly Mg-ilmenite, with Cr-pyrope and chromite, and lesser amounts of Cr-diopside and minor olivine. Indicator minerals are most abundant to the southwest to southeast of the two kimberlites and form a fan-shaped dispersal pattern that extends at least 6 km, and potentially 30 km down-ice. The results presented here demonstrate how ice-flow mapping can be combined with indicator mineral abundance, mineral chemistry, and relative abundance data to define dispersal patterns from kimberlite.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".