Bibliographic record
Abstract
The symposium focused on newly released critical continuous soil gas monitoring data associates with residential and industrial activity around the world. Multiple representatives from the United Kingdom, Canada, Germany, Brazil, etc., participated in the Symposium. From oil and gas companies, chemical companies through small industrial sites, there is a growing need to understand and mitigate worst case/explosive or high human health risk conditions. Dry cleaners, gas stations, refi neries, fracking sites, landfi lls, landfi ll energy systems, machine shops, etc., all can exhibit Vapor Intrusion (VI) risk. Often driven by litigation, the interest in VI into homes and buildings has skyrocketed. Groundwater cleanup costs are dwarfed by the potential for class action VI suits. Recent dynamic risk observations pose serious implications about conventional approaches, best management practices, due diligence and formerly closed sites, and create a need to identify and understand site-specifi c conditions that warrant continuous monitoring. As such, several regulatory entities are now advocating for continuous VI monitoring and formerly closed sites with no further action letters are being reopened. The forthcoming reduction in the MCL's of TCE and its designation as a human carcinogen will have a dramatic effect on environmental site characterization, remediation and litigation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.864 | 0.810 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".