Comparison of Sampling Methods to Determine Total and Speciated Mercury in Flue Gas, CRADA 00-F038 Final Report
Bibliographic record
Abstract
The U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL) and Frontier Geosciences, Inc. (FGS) collaborated in the investigation of sampling techniques that measure total and speciated forms of mercury (Hg) in flue gas. The FGS techniques investigated are referred to as the Frontier Sorbent Mercury Speciation (FSMS) method and the Sorbent Total Mercury (STM) method (Prestbo et al. 2001). Testing was conducted over five consecutive days during the week of March 27, 2000, on the 500 lb/hr pilot-scale coal combustion facility located at NETL-Pittsburgh. As a standard for comparison with the FSMS and STM methods, a standardized, draft ASTM method (ASTM 1998), referred to as the Ontario-Hydro (O-H) method, was run simultaneously at the outlet of the pilot unit baghouse. For each O-H sample, two FSMS mercury speciation traps and one STM trap were run. Following sampling, FGS analyzed the FSMS and STM samples, and NETL analyzed the O-H samples. These analytical results from FGS and NETL were combined with sampling data to calculate flue gas mercury concentrations and were then compared. This report presents the results of that comparison.
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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 | 0.012 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".