Geological Survey of Canada till-sampling and analytical protocols: from field to archive, 2020 update
Bibliographic record
Abstract
For more than 50 years, researchers at the Geological Survey of Canada (GSC) have developed, tested, and refined till geochemical and indicator mineral methods as applied to mineral exploration, provenance studies, and environmental research in glaciated terrain across Canada. This cumulative experience and knowledge were used to produce and publish the GSC's first comprehensive field and laboratory methods protocol manual for till geochemical and mineralogical surveys in 2011. The publication being presented here provides an update and augmentation of this earlier version and presents the major concepts of till as a sample medium, glacial dispersal, and field and laboratory procedures. These protocols are used by the GSC to guide till sample collection, sample processing, geochemical and indicator mineral analyses, implementation of quality assurance/quality control (QA/QC) procedures, archiving methods, and data reporting by the Geological Survey of Canada. Using consistent sample media and making diligent field notes and observations are also considered fundamental to the protocols, and are presented herein. The protocols will be of value to provincial/territorial government geological agencies, the mineral exploration industry, and academia and we hope they will benefit from the use of this manual. Adopting a common set of protocols allows the GSC, other researchers, and exploration geologists to directly compare till geochemical and indicator mineral data sets from various parts of Canada and ensures proper minimum levels of QA/QC for all till geochemical and mineralogical 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 | 0.027 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.020 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.024 | 0.021 |
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".