Acid Mine Drainage Index (AMDI): a benthic invertebrate biotic index for assessing coal mining impacts in New Zealand streams
Bibliographic record
Abstract
Abstract Acid mine drainage (AMD) is a widespread phenomenon globally. Drainage into streams from coal mines often contains a cocktail of acidic waters high in dissolved metals, and consequently stream invertebrate communities may be severely impacted. Traditionally, the intensity of impacts has been assessed by combinations of water chemistry and benthic invertebrate metrics; however, a metric specifically designed for assessing mining impacts has not been developed. We propose a benthic invertebrate biotic index: the Acid Mine Drainage Index (AMDI), based on species presence data. The AMDI has been developed by associating water chemistry and benthic invertebrate community data collected from 91 sites. AMD indicator scores for 57 taxa were calculated using weighted averaging. Site scores can range from 0 (severely impacted) to 100 (unimpacted) and sites can be categorised as ‘severely impacted’, ‘impacted’ or ‘unimpacted’. Comparisons between AMDI and traditional indices indicated the AMDI is more accurate at detecting mine drainage.
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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 | 0.003 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".