Bibliographic record
Abstract
Canada's nuclear history begins with geology, but it does not begin with uranium.Canada was a storehouse of minerals, mostly embedded in the Canadian Shield, with mining companies to match.In the early twentieth century, these companies found a home in Toronto -a large home, centred on the Toronto Stock Exchange, where mining stocks were born, flourished, and, not infrequently, died.Mining was a speculative business, which is to say, risky.Prospectors, promoters, and speculators were thick on the ground, and their projects far outnumbered viable mining firms.But there were enough of these, and by the 1920s Canada had developed a human and technological infrastructure of miners, mining engineers, and even a very few geologists, who could point the way to ores and, it was hoped, wealth.The wealth was displayed in large houses in the new suburbs of Canada's biggest cities, Toronto and Montreal.Eldorado Gold Mines Limited was a typical speculation of the 1920s.A prospector-speculator named Gilbert LaBine claimed that gold was to be found at a certain location in Manitoba, and raised money accordingly, in both Canada and the United States.His mine was not viable, and Eldorado Gold Mines might have joined the long parade of failed mines in Canada.But LaBine knew how to read geological reports, and he had read of a new element, derived from uranium in pitchblende -radium.Radium was the wonder drug of the 1920s -one of the few that could be used to treat cancer, although it was recognized that it could cause cancer as well.It was hard to produce, but at one point in the 1920s it sold for $120,000 a gram and
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.752 | 0.679 |
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".