National mineral potential assessment for sediment-hosted copper mineral systems in Australia Version 1.0
Bibliographic record
Abstract
Sediment-hosted copper (Cu) mineral systems are important sources of base metals and critical minerals such as cobalt that are vital to delivering Australia’s low-carbon economy. In Australia, sediment-hosted Cu resources account for ~11% of the total Cu resources. Given their significance to the Australian economy, national-scale mineral potential models for sediment-hosted Cu have been developed. In addition to the potential for sediment-hosted Cu mineralisation, the uncertainty related to data availability has been examined. Three mineral potentialmodels derived from the combination of two mineral systems have been derived from a large volume of precompetitive geoscience data combined with mineral systems expertise, each using a different combination of input maps to assess the influence of incomplete data on the results. The mineral potential models successfully predict the location of major sediment-hosted stratiform Cu and Mount Isa-type Cu deposits while highlighting new areas of elevated prospectivity in under-explored regions of Australia, reducing the exploration search spaceby up to ~84%.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".