Optimal ferromagnetic fraction in till samples along ice-flow paths: case studies from the Sue-Dianne and Thompson deposits, Canada
Bibliographic record
Abstract
Iron oxides are minerals resistant to chemical alteration and mechanical abrasion, and which have ferromagnetic properties and a range of chemical compositions. These characteristics are useful as indicator minerals in exploration, for example using till in glaciated terrains. Iron oxide proportions, grain size, and chemical composition of till samples collected near the Sue-Dianne Cu-Au-Ag IOCG deposit in the Great Bear magmatic zone (Northwest Territories, Canada) and magmatic Ni-Cu deposits in the Thompson Nickel Belt (Manitoba, Canada) show that subsamples containing c. 100 grains from the 0.25–1.0 mm grain size ferromagnetic fraction yield a representative mineralogical and compositional range of oxide grains from a till sample. Subsamples with less than 100 grains yield statistically less representative data. The 1–2 mm grain size fraction typically contains too few iron oxide grains and thus using this fraction is not statistically representative. The composition of iron oxides from eight till and five bedrock samples was determined along transects up- and down-ice of the Cu-Au-Ag Sue-Dianne IOCG deposit. At, and immediately down-ice of, the deposit, hematite is the principal oxide and shows dominant BIF and IOCG chemical signatures in the Ca+Al+Mn v. Ti+V discriminant diagram. Up-ice and farther down-ice of the deposit, magnetite and titanomagnetite are the dominant oxides and magnetite shows dominant Kiruna and IOCG signatures. The composition of iron oxides from six till samples along a north–south transect and 11 till samples from a 180 km-long east–west transect, along the older and younger directions of ice-flow, respectively, was determined in the Thompson Nickel Belt (Manitoba, Canada). The proportion of magnetite in till with the signature of Ni-Cu deposits increases for at least 1 km south of the Pipe Ni-Cu deposit along the direction of the older southward ice flow, whereas the glacial dispersal of magnetite with a chemical signature typical of Ni-Cu deposits was limited during the younger westerly ice flow.
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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 | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".