Bibliographic record
Abstract
Although world mineral exploration expenditure for non-ferrous commodities has been recovering strongly from its low in 2009 and is back on the rising trend which commenced in 2002, Australia has continued to lose ground relative to other global and competitive exploration destinations. Australia’s share of global exploration for non-bulk commodities has virtually halved from its peak of 21 % in 2002 and it now stands at a mere 12 % of the total, while that of Canada, for instance, has increased from 14 % to 18 % over the same period. Recent Australian Bureau of Statistics figures indicate that Australian exploration expenditure fell during the March 2012 quarter in all states and for all commodities, particularly for iron ore and coal. While the March quarter is generally a period of low expenditure due to climatic reasons, the seasonalised figures still portray a pattern of sluggish investment in exploration. Falls were greater in Queensland and Western Australia, which is probably attributable to the impending introduction of the MRRT and the recent softening of iron ore and coal prices. Given that bulk minerals now make up half of the exploration dollars spent in Australia, a sustained contraction in this sector will have a material impact on employment and service providers in the broader economy. While original exploration expenditure rebounded in the June quarter, in seasonally adjusted terms the declining
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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) | 0.002 | 0.004 |
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; both teacher heads agree on what is shown here.
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".