Detailed Field Investigation of Vapor Intrusion Processes
Bibliographic record
Abstract
The purpose of this demonstration was to validate improved vapor intrusion field investigation methods to support cost-effective evaluation of the vapor intrusion pathway. Intensively monitored sites, such as the Borden Landfill in Canada, have greatly contributed to our understanding of the physical and chemical processes that control the transport of chemicals in groundwater. For this project, we have used a similar approach (i.e., intensively monitored sites with specially designed monitoring networks) to address the critical groundwater-to-indoor-air vapor intrusion pathway. The primary goal of the project has been to support the development of refined vapor intrusion guidance, stepwise screening, and cost-effective field investigation approaches. This will benefit facility managers by providing investigation results that support a defensible evaluation of vapor intrusion. Determination of the presence or absence of vapor intrusion impacts is important to the site management process. Definitive determination of the absence of vapor intrusion allows resources to be directed to other site impacts while avoiding presumptive mitigation, which can be burdensome from both financial and public relations perspectives. The primary objective of this demonstration study was to identify a cost-effective and accurate protocol for investigation of vapor intrusion into buildings overlying contaminated groundwater. Three performance goals were established, and all objectives were met, namely, *Collection of data representative of site conditions *Determination of vapor intrusion impacts at demonstration sites (i.e., indoor air concentration of chemical above risk-based screening limit, not attributable to background indoor air sources) *Development of a reliable vapor intrusion investigation approach (i.e., identify a limited scope investigation approach with higher accuracy than current approaches).
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".