FIELD RATA TESTING WITH THE MERCURY INSTRUMENTAL REFERENCE METHOD
Bibliographic record
Abstract
In June 2007, the EPA released draft Method 30A – Determination of Total Vapor Phase Mercury Emissions from Stationary Sources. Coal-fired power generators installing mercury CEMs are required to complete certification testing under the Clean Air Mercury Rule (CAMR) prior to January 1, 2009, including relative accuracy test audits (RATAs). The issued draft M30A, a work-in-process document, is offered as an option for RATA testing. ADA-ES, Inc. has developed a portable mercury CEM system for use as an Instrumental Reference Method (IRM) as described in Method 30A in response to industry needs. This effort was conducted through a DOE NETL Clean Coal Power Initiative (CCPI) at We Energies Presque Isle Power Plant. A Thermo mercury CEM has been installed and operating at Presque Isle since June 2005 on the combined flue gas from Units 7, 8, and 9. The IRM was tested at Presque Isle in June 2007 in conjunction with Ontario Hydro RATAs on the installed CEM. Sorbent Trap Method measurements (EPA draft Method 30B) were also collected. This paper provides a discussion of draft Method 30A illustrated with results from the IRM RATA testing at Presque Isle including traversing, system integrity testing, and dynamic spiking. Performance of the installed mercury CEM, Ontario Hydro RATA, and M30B RATA results will also be presented.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".