Thallium isotopic compositions as tracers in environmental studies: A review
Bibliographic record
Abstract
Thallium is a highly poisonous heavy metal. Since Tl pollution control has been neglected worldwide until the present, countless Tl pollutants have been discharged into the environment, endangering the safety of drinking water, farmland soil, and food chain, and eventually posing a great threat to human health. However, the source, occurrence, pathway and fate of Tl in the environment remains understudied. As Tl in non-contaminated systems and from anthropogenic origin exhibits generally different isotopic signatures, which can provide fingerprint information and a novel way for tracing the anthropogenic Tl sources and understanding the environmental processes. This review summarizes: (i) the state-of-the-art development in highly-precise determination analytical method of Tl isotopic compositions, (ii) Tl isotopic fractionation induced by the low-temperature surface biogeochemical process, (iii) Tl isotopic signature of pollutants derived from anthropogenic activities and isotopic fractionation mechanism of Tl related to the high-temperature industrial activities, and (iv) application of Tl isotopic composition as a new tracer emerging tracer for source apportionment of Tl pollution. Finally, the limitations and possible future research about Tl isotopic application in environmental contamination is also proposed: (1) Tl fractionation mechanism in different environmental geochemistry processes and industrial activities should be further probed comprehensively; (2) Tl isotopes for source apportionment should be further applied in other different high Tl-contaminated scenarios (e.g., agricultural systems, water/sediment, and atmosphere).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".