DISCUSSIONS ORIGIN OF YELLOWKNIFE GOLD DEPOSITS
Bibliographic record
Abstract
Sir: I have read with interest McConnell's contribution (this journal vol. 59, p. 328) to the problem of the origin of the Yellowknife gold deposits. While the occurrence of gold in granites described in this note appears to be a new discovery, the fact that gold is present in shear zones in the granitic rocks at Yellowknife is not novel. Gold in shear zones in granitic rocks and granite dikes was first noted by Jolliffe (2) and later described in my memoir (1). Furthermore, when I was working in the Yellowknife-Gordon Lake area I noted specks of gold and a few sulfides in narrow shear zones in many types of granitic rocks. As the reader is probably aware the occurrence of gold and silver veins in granite and porphyry is a common phenomenon. I might mention here the very profitable orebodies at the Renabie Mine in Ontario (in granite gneisses), the famous deposits at Kirkland Lake (partly in synenite), the Beaverdell silver deposits in British Columbia (in quartz diorite), and a number of silver deposits in the granitic rocks of the Slocan district, British
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".