Cattle grazing on reclaimed mine tailings at Highland Valley Copper : a review
Bibliographic record
Abstract
Revegetation and sustainable cattle grazing are major objectives in the program for the reclamation of mine tailings at the Highland Valley Copper mine in British Columbia, Canada. Residual molybdenum (Mo) in the tailings is imbibed by vegetation and can accumulate to extremely high levels (> 25 ppm Mo on a dry matter basis). Accordingly, grazing studies were initiated with cattle to determine the feasibility of utilizing the Bethlehem and Highmont tailings sites for livestock production. Molybdenum levels in forages were at least ten times higher at Highmont than at Bethlehem. A total of 262 cow-calf pairs grazed the Bethlehem site for four consecutive years (1994 - 1997) and the Highmont site for five consecutive years (1998 - 2002). Cattle at Bethlehem did not show clinical signs of Mo toxicity or copper deficiency. In contrast, cattle at Highmont showed clinical signs including lameness, diarrhea and haircoat depigmentation. The onset and severity of the affliction appeared to be related, in part, to prevailing moisture conditions, which affected Mo availability in forage. The cattle recovered by the end of each trial and haircoat problems were resolved by the next spring. Preventive measures were attempted using copper supplements that can alleviate Mo toxicity. Copper boluses did not provide adequate protection in 2001 but copper sulphate supplementation in loose salt prevented the onset of clinical signs in 2002.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".