Airborne Inductive Induced Polarization Chargeability Mapping of VTEM Data
Bibliographic record
Abstract
Airborne inductive induced polarization (AIIP) effect has been widely recognized in airborne time domain EM system data. AIIP chargeability mapping opens new and exciting areas in mineral exploration for airborne time domain EM systems in the search for sulphides and clay minerals. An AIIP chargeability mapping tool based on CSIRO/AMIRA Airbeo is created for VTEM data, with examples from Mt Milligan, British Columbia, Canada and Tullah, Tasmania. Using the Cole-Cole frequency dependent resistivity, the tool examines the VTEM decay data spectrally and selects the decay associated with the lowest RMS error from a set of decays generated by varying chargeability m and time constant T within specific ranges, giving a constant frequency factor c, while the background resistivity is inverted. The parameter mo used to generate the decay is the AIIP apparent chargeability.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".