Distance to Highway and Factory Density Related to Lung Cancer Death and Associated Spatial Heterogeneity in Effects in Jiading District, Shanghai
Bibliographic record
Abstract
Abstract Objective This study aimed to explore distance to highway and factory density related to lung cancer (LC) death and their spatial heterogeneity in effect. Methods We conducted a retrospective cohort study by using the data of registered LC patients in Jiading District from 2002 to 2012. Standard parametric model with weibull distribution was used to explore factors related to LC death and the spatial effect of environmental factors were detected by using spatial survival analysis. Results Shorter distance to highway (aOR = 1.15, 95% CI:1.03–1.30) and higher factory density (aOR = 1.20, 95% CI:1.05–1.37) were significantly associated with increased risks of LC death, and the associations showed spatial differences in northern and southern areas of Jiading District, respectively. High-risk areas were mainly distributed in the suburbs with a low population density, while low-risk areas were primarily located in the urban areas. Conclusion Traffic and factory-related pollution was significantly associated with increased risk of LC death with an obvious spatial heterogeneity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".