China’s most typical nonferrous organic-metal facilities own specific microbial communities
Bibliographic record
Abstract
The diversity and function of microorganisms have yet to be explored at non-ferrous metal mining facilities (NMMFs), which are the world's largest and potentially most toxic sources of co-existing metal(loid)s and flotation reagents (FRs). The diversity and inferred functions of different bacterial communities inhabiting two types of sites (active and abandoned) in Guangxi province (China) were investigated for the first time. Here we show that the structure and diversity of bacteria correlated with the types of mine sites, metal(loid)s, and FRs concentrations; and best correlated with the combination of pH, Cu, Pb, and Mn. Combined microbial coenobium may play a pivotal role in NMMFs microbial life. Arenimonas, specific in active mine sites and an acidophilic bacterium, carries functions able to cope with the extreme conditions, whereas Latescibacteria specific in abandoned sites can degrade organics. Such a bacterial consortium provides new insights to develop cost-effective remediation strategies of co-contaminated sites that currently remain intractable for bioremediation.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".