Bibliographic record
Abstract
This volume describes the use of till geochemical and indicator mineral methods for mineral exploration in glaciated terrain of Canada. The principles and examples described in this volume wil have direct applications for exploration companies and prospectors exploring for diamonds, precious and base metals and uranium in glaciated parts of North America, northern Europe and Asia and mountainous regions of South America. The first two papers in this volume provide an introduction to glaciated terrain and the two styles of glaciation that have affected the world, continental glaciers in broad flat lying Shield areas and alpine glaciers in mountainous terrain. Sampling techniques are described next, followed by an introduction to the use of heavy minerals. Heavy mineral methodss have become an important exploration tool in glaciated terrain for gold and base metals and, in the last ten years, for diamonds. Lake sediments and biogeochemical methods are also included in this volume as a complement to geochemical and indicator mineral methods in glaciated terrain. A chapter on GIS has been included because data interpretation and display are important and essential parts of any regional or detailed geochemical survey. The remainder of the volume is case studies for the three main glaciated terrain tyes in Canada: Shield, Appalachia and Cordillera
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.799 | 0.743 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".