Effect of Occupational Manganese Exposure on Cognitive Function in Male Smelting Workers
Bibliographic record
Abstract
[Objective]To explore the changes of cognitive function in male smelting workers with exposure to various levels of manganese(Mn) and its possible influencing factors.[Methods]A total of 240 male smelting workers were chosen from a Mn smelter in Guangxi and divided into high(86 workers) and low(154 workers) Mn exposure groups according to a cumulative exposure index(CEI);240 male workers of a sugar refinery in the same region were selected as the control group.All participants were required to complete questionnaires to collect general information and evaluate cognitive function by the Montreal Cognitive Assessment(MoCA) test(Beijing version).[Results]There was a negative association between cognitive function and the Mn cumulative exposure levels in male smelting workers(r=-0.324,P0.05).The MoCA scores of the 2 exposure groups were remarkably lower than that of the control group(P0.01),and the group with high Mn exposure level reported significantly lower scores than the group with low Mn exposure level(P0.05),after adjusted age,marital status,and other related variables.The results of multiple linear regression analysis showed that the worker’s cognitive function was significantly affected by age,education,Mn exposure level,and smoking(P0.05).[Conclusion]Occupational Mn exposure might decrease the cognitive function in male smelting workers.Moreover,the cognitive function could also be affected by age,education,and smoking.
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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 | 0.001 |
| 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 | 0.000 |
| 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".