Modeling the Shape of the Dependency of Airborne Benzene Concentration in the Air on Distance to Primary Oil and Gas Facilities
Bibliographic record
Abstract
The level and determinants of airborne concentrations were estimated by collecting air samples at 1206 fixed sites across a geographic area associated with primary oil and gas industry in the rural western Canada, in the provinces of Alberta, north-east British Columbia, and central and southern Sasketchewan from April 2001 to December 2002. Benzene concentrations integrated over one calendar month were determined using passive organic vapor monitors. Previous work applied linear mixed effects models to identify the determinants of airborne benzene concentrations, in particular the proximity to oil and gas facilities. We present results of a more flexible model using cubic splines to accommodate nonlinearities in the effects of determinants of airborne benzene concentrations, as well as time. Benzene concentrations exhibited monotonically increasing time trends for the months from July through December, and monotonically decreasing time trends corresponding to the months from December to July. We illustrated here how cubic splines can be used to identify complex relations between proximity to point sources of air pollution and observed extent of contamination, during the study period, and identified batteries as an important source of benzene emissions that was missed in previous analysis of the same data. These findings contribute to better understanding how positioning oil and gas facilities impacts air quality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".