Understanding Archean greenstone-hosted lode gold mineralization in Ontario Canada through helicopter TDEM data
Bibliographic record
Abstract
SummaryWe have analysed s large public-domain TDEM datasets acquired by Ministry of Northern Development and Mines – MNDM of Ontario Canada. Geophysical data set 1076 (6,500 out of the original 10,000 line-kms not affected by powerlines) located in an area east of Nestor Falls Ontario in the Western Wabigoon Terrane (WWT) for the purpose of understanding the potential deposition sites of possible gold mineralization. There are a large number of known mineral occurrences (mostly gold) in the Nestor Falls survey area. By analysing these two datasets, we try to determine the electromagnetic, magnetic and airborne inductively induced polarization (AIIP) signatures directly or indirectly related to the gold showings.The results of the investigation indicate that some of the Archean lode gold showings are located at some distance away from the strongest conductors and others don’t have any conductive signatures at all. The magnetic association is complex and the gold mineralization could be with or without magnetic signatures. Many Canadian Archean lode gold occur in resistive glaciated terrains, and sometimes show weak AIIP responses that can be seen in the Logrestau and Restau products. We believe that the EM, magnetic and the AIIP Logrestau or Restau signatures, if detected and interpreted properly, could potentially be used as proxies in the search for Archean greenstone-hosted lode disseminated gold mineralization in Ontario, and perhaps in other Archean terranes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".