Redox-induced spontaneous polarization as a cause of large self potential anomalies over disseminated sulphides and other buried features
Bibliographic record
Abstract
University of Ottawa, Ottawa, Ontario. Self potential (SP) has been used for over 150 years as a passive geophysical exploration tool but the cause of SP anomalies over sulphide ore bodies remains the subject of debate. The most prevalent theory for their formation is the dipole model (Figure 1) which argues that the difference in oxidation potential between the top and bottom of a metallic ore body results in upward movement of electrons through it, and a return current in the surrounding country rock. For reasons described below, SP dipoles should not exceed about 400 mV above sulphides or slightly more above graphite. Also, according to the dipole model, disseminate sulphides should produce no SP phenomenon at all because a continuous metallic or semi-metalically bonded conductor between the oxidants and reductants is required. Thus, the dipole model has been recognized as problematic for decades since disseminated sulphides are often reported to have large SP anomalies not uncommonly exceeding 1000 mV (e.g. Corry, 1985; Goldie, 2002). Many numerical SP models exist but these largely describe the responses to be expected on surface due to buried polarized metallic bodies of various shapes, attitudes and depths. The models do not generally attempt to describe the cause of the polarization in the first instance and are therefore empirical. Also, since they are ultimately based on the dipole
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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 | 0.000 |
| 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 | 0.001 |
| 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 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".