Halogenated POPs and PAHs in Blood Plasma of Hong Kong Residents
Bibliographic record
Abstract
The objective of this study was to quantify organic chlorinated pesticides (OCPs), polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), and polycyclic aromatic hydrocarbons (PAHs) in blood plasma collected from 111 healthy residents in Hong Kong to assess the levels of these pollutants in the general population during the period of March to April, 2008. Concentrations of these residues in blood plasma obtained from the Hong Kong Red Cross Blood Transfusion Service were determined by gas chromatography-mass spectrometry. Naphthalene, phenanthrene, p,p'-DDE, PCB-180, and PBDE-47 were detected in 100% of the participants. Females had significantly greater concentrations of acenaphthylene (female: 93.3 ng/g lipid; male: 39.8, p < 0.05), anthracene (22.3; 15.3, p < 0.05), fluoranthene (138; 125, p < 0.05), p,p'-DDE, p,p'-DDT, PCB-183, BDE-99 than males. Blood of smokers contained significantly greater (p < 0.05) concentrations of acenaphthene, benzo(a)pyrene, p,p'-DDE, p,p'-DDT, PCB-138, BDE-47, and BDE-99 than did blood of nonsmokers. Positive correlations were found between concentrations of each class of pollutant, with respect to seafood diet habit, Body Mass Index (BMI), and age. Concentrations of HCHs and DDTs in blood plasma of healthy Hong Kong residents were greater than those of other countries, and it was found that smoking, consumption of a seafood diet, BMI, and age could influence concentrations in human blood.
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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 | 0.000 | 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".