Application of Machine Learning and Pyrite Geochemistry to the Identification of Paleoplacer Gold Sources at Pardo, Ontario, Canada
Bibliographic record
Abstract
Fluvial conglomerate of the Huronian (2.45-2.20 Ga), Mississagi Formation from the southern Cobalt Basin in Pardo and Clement townships, Ontario, hosts detrital pyrite, uraninite, and free gold derived from an unknown source. This study aimed to determine the source of gold by using detrital pyrite as a proxy. To do this, pyrite was characterised, texturally and geochemically from the Mississagi Formation and potential sources within the Neoarchean basement. A Random Forest statistical classifier algorithm, trained on a global dataset, predicted pyrite classes mainly split between VMS (57%) and orogenic (39%), with minor input from epithermal-porphyry-skarn (3%), and sedimentary-hosted (0.6%) for detrital pyrite at Pardo. Textural and geochemical clues also point to similarity in some detrital samples with both VMS and orogenic style mineralization at Golden Rose, a former banded iron formation-hosted gold mine located 15 km north of Pardo.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".