Bibliographic record
Abstract
On May 30th of 2014 we lost a truly gifted and outstanding geochemist, pioneer, loyal friend, co-founder of the Association of Applied Geochemists (then the Association of Exploration Geochemists, AEG, and now AAG), and founder of the Association’s first journal, the Journal of Exploration Geochemistry (JGE): Eion M. Cameron. Most of Eion’s long and illustrious career was spent at the Geological Survey of Canada (1966–2000) as both a research geochemist and as Head of the Applied Geochemistry Subdivision, comprising some 32 scientists and technical staff. A major emphasis of Eion’s research was on the development, testing and application of new and improved methods of detecting ore deposits both at surface and buried at depth. His accomplishments in this area are diverse. For example, he established lake sediment and water geochemistry as an effective mineral exploration tool in Canada’s north. In 1972, Eion carried out the first regional-scale geochemical survey in Canada, sampling lake sediments and waters over 93 000 km2 of the Northwest Territories in only six weeks with three choppers and one float plane. Some of the discoveries, as a result, are the Yava and Hackett River VMS deposits. This survey paved the way for Canada’s National Geochemical Reconnaissance Program. Still in the 1970s, he led the first GSC multi-disciplinary multi-agency …
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.134 | 0.050 |
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".