Use of Till Geochemistry and Mineralogy to Outline Areas Underlain by
Bibliographic record
Abstract
Abstract — Wawa has long been a center of mineral exploration activity and diamonds have been reported in the area since the 1930s. However, diamond exploration did not begin in the area in earnest until 1991. In 1993, Sandor Surmacz and Marcelle Hauseux of Saminex began a prospecting program in the area which culminated in their discovery of the “Sandor ” diamond occurrence in an outcrop on the east side of the Trans-Canada Highway. They subsequently optioned the property to Spider Resources Inc. who obtained the necessary exploration permits from Algoma Central Corpo-ration and undertook an exploration program. The diamonds at the “Sandor ” diamond occurrence are hosted in the matrix of a spessartite dike composed of actinolite, biotite, and albite. Of the 64 simi-lar dikes that have been sampled and analyzed to date, eight have been found to contain a total of 231 diamonds. Most of the diamonds are of high quality, although they are small. The dikes are non-magnetic and do not have any other geophysical characteristic that can be used to differentiate them from the adjacent country rock. All of the dikes discovered to date have been found by prospecting or by geological mapping by the Ontario Geological Survey. The dikes do not contain pyrope garnet or chrome diopside, two of the commonly used kimberlite indicator minerals. Instead, low Mg, high Cr, Zn-rich chromite, and ilmenites of variable composition, some of which
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".