INTEGRATED SYSTEM TO CONTROL PRIMARY PM 2.5 FROM ELECTRIC POWER PLANTS
Bibliographic record
Abstract
Mercury measurements were made by Southern Research Institute and conformed to the Ontario Hydro Method. EPA's current Reference Method 29A is for total mercury, whereas the Ontario Hydro procedure is capable of identifying the composition and species of the total mercury. One of the disadvantages of the Ontario Hydro Method is that it requires several weeks to complete the full analysis due to its extensive laboratory procedures. Mercury measurements were also obtained with a PS Analytical Continuous Emission Monitor (CEM) owned by the U.S. EPA and contributed to this project by EPA's fine particulate group in Research Triangle Park. The PSA CEM functions on the principle of atomic fluorescence and is capable of measuring trace concentrations of mercury in water or air. The instrument was setup to monitor elemental and total mercury at the dry scrubber inlet and ElectroCore outlet. Each cycle required about 20 minutes to complete. Thus, the monitoring was not in ''real time'' in a strict sense, but did provide mercury tracking in continual batch processing. Particulate measurements were determined by EPA Method 5 as well as with a P5A continuous monitor. The P5A is on loan to the project through EPA and SRI. Calibration factors for the device were provided by SRI. All particulate data was analyzed and interpreted by LSR Technologies, with technical input from Armstrong Environmental and SRI.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.058 | 0.017 |
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".