Mining to mud: a multidisciplinary approach to understanding Victoria’s riverine landscape as a product of historical gold mining
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Victorian gold rush began in 1851, resulting in massive demographic, land use, and social changes (Serle 1968). Rivers, during much of the gold mining history of Victoria, were used as a “free” resource, both to extract and process sediment. The effect on river systems around the state was catastrophic. A quarter of the length of the main streams was damaged. Even though the devastating environmental impact of Victorian gold mining was recognised at the time, it appears to have been forgotten today (Figure 1). This is despite extensive documentation of the number of mining operations, methods used, resultant environmental impacts and consequent legislation. The ARC discovery project “Rivers of gold” set up a multi-disciplinary team to try and reconstruct the historical development of mining across the state of Victoria, and to determine the legacy of this mining.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it