Laser Ablation Inductively Coupled Plasma Mass Spectrometric Analyses of Base Metals in Arctic Char (Salvelinus alpinus) Otoliths Collected from a Flooded Base Metal Mine
Bibliographic record
Abstract
Otoliths from arctic char recovered from the water body formed from an abandoned open-pit nickel-copper mine contain a trace element record related to the geology of the immediate watershed, past mining activity in the area, and the fish's diet. Laser ablation inductively coupled plasma mass spectrometric analyses across the annular structure of the otoliths detected trace amounts of nickel, copper, and chromium believed to be related to the metal-bearing, mafic-ultramafic minerals in the pit. Oscillatory strontium, barium, and zinc profiles may reflect changing water temperature, diet, or fish metabolism. Lead was detected in very low concentrations and may be related to anthropogenic influence. This closed lake system provides a unique opportunity to study an introduced exotic species in a setting where neither migration nor recruitment have been possible. The fish have successfully occupied the lake and continue to breed despite the influence of the surrounding rocks and local contamination. The chemical record retained within otoliths provides a method of monitoring trace elements affecting fish on a yearly basis and may be regarded as a useful assessment tool for examining the exposure of wild organisms to trace elements.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".