Till sampling and geochemical analytical protocols used by the Geological Survey of Canada
Bibliographic record
Abstract
The Geological Survey of Canada (GSC) has developed field and lab methods protocols to guide till sample collection, processing, geochemical analysis of the till matrix, monitoring of quality assurance/quality control, and archiving procedures for reconnaissance- to local-scale geochemical surveys. The most significant concepts and procedures are described in this paper. Continued and long-term use of these protocols will ultimately allow GSC researchers to integrate and contrast multiple datasets and ensure minimum levels of quality assurance and control for all till geochemical data. This set of protocols is the first established for Canadian till sampling and analysis and represents a contribution to the GSC’s Geo-mapping for Energy and Minerals (GEM) Program. Sharing the GSC’s knowledge on till sampling and analysis with the international community will allow other researchers and explorationists to adopt similar procedures. This sharing of knowledge will ultimately allow comparison of till geochemical datasets from various parts of Canada and internationally as well as ensuring a minimum level of quality assurance and control for all till geochemical data.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.015 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.008 |
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".