Processing of glacial sediments for the recovery of indicator minerals: protocols used at the Geological Survey of Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A successful method of mineral exploration in glaciated terrain is the use of indicator minerals recovered from carefully selected glacial sediments, and subsequently traced back to their bedrock source. The successful application of indicator mineral methods relies on efficient and effective recovery as well as the correct identification of a wide variety of indicator minerals. The Geological Survey of Canada (GSC) has developed protocols for ongoing and future research projects to achieve the highest quality for reporting indicator mineral data. Such protocols include the use of field duplicate samples, blank samples, and base material spiked with known numbers, morphologies, species, and sizes of indicator minerals. Field duplicate samples serve to estimate sediment heterogeneity. Spiked samples are used to monitor the accuracy of the sample processing and mineral identification methods for recovering specific minerals. Blank samples serve to detect potential carry-over contamination. In certain instances, a specific sample processing order is essential and should be communicated to the commercial processing laboratory. Ore-rich samples collected near known mineralization are to be processed last, to reduce chances of carry-over contamination. Repeated indicator mineral counts should be carried out on at least 10% of the heavy mineral concentrates to measure reproducibility (precision) of the mineral counts. All indicator mineral data, original laboratory reports, heavy mineral concentrates, unmounted picked grains, and grain mounts are now archived at the GSC, using specific guidelines.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it