Integrated interpretation applied to the Nardoo prospect, QLD.
Bibliographic record
Abstract
Integrated interpretation plays a vital role in maximising the value from geoscience exploration datasets. In some cases, integrated interpretation refers to the idea of bringing a wealth of geological constraints, petrophysical constraints and geophysical datasets together into a common earth model. In other cases, particularly beneath cover, the availability of geological and petrophysical constraints is often limited, and geophysics plays a much larger role. The process of integrated interpretation then refers to the careful process of deciphering the key, often sparse, geological and petrophysical information, and determining how they relate to the geophysics, then capitalising on these relationships to develop a geological model consistent with all the geophysics and a priori information. The resulting model is less ambiguous than those that could have been derived from any of the input datasets considered in isolation. The purpose of this paper is to outline integrated interpretation concepts as applied to the Nardoo prospect in Queensland, approximately 215 kilometres north of Mt Isa. The area is covered by ground gravity, ground EM and airborne magnetic surveys. There is no outcrop within the area of interest, and at the time the work was completed, there was only a single drillhole (water bore) and no petrophysical data. The magnetic signatures appear to be affected by remanent magnetisation. Even in this adverse scenario, careful consideration of all the inputs and using the concepts behind integrated interpretation can lead to development of a geologically based exploration model. The resultant model explicitly incorporates cover, and magnetic basement domains, each attributed with magnetic remanence parameters derived through modelling and inversion.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".